Initiating Background Updates Based on User Activity

ABSTRACT

In some implementations, a mobile device can be configured to monitor environmental, system and user events. The occurrence of one or more events can trigger adjustments to system settings. In some implementations, the mobile device can be configured to keep frequently invoked applications up to date based on a forecast of predicted invocations by the user. In some implementations, the mobile device can receive push notifications associated with applications that indicate that new content is available for the applications to download. The mobile device can launch the applications associated with the push notifications in the background and download the new content. In some implementations, before running an application or accessing a network interface, the mobile device can be configured to check energy and data budgets and environmental conditions of the mobile device to preserve a high quality user experience.

INCORPORATION BY REFERENCE; DISCLAIMER

Each of the following applications are hereby incorporated by reference:application Ser. No. 14/253,781 filed on Apr. 15, 2014; application No.61/832,932 filed on Jun. 9, 2013. The Applicant hereby rescinds anydisclaimer of claim scope in the parent applications or the prosecutionhistory thereof and advises the USPTO that the claims in thisapplication may be broader than any claim in the parent applications.

TECHNICAL FIELD

The disclosure generally relates to adjusting components of a computersystem based on user behavior.

BACKGROUND

Mobile computing devices are typically battery operated. Some mobilecomputing devices can wirelessly access network resources over cellulardata and/or Wi-Fi network connections. These mobile devices are oftenconstrained by battery capacity and limits on cellular data.

Some mobile computing devices allow a user to run applications thataccess data from network resources. The user typically invokes anapplication and then must wait for the application to retrieve data fromthe network resources so that the application can present currentupdated content.

SUMMARY

In some implementations, a mobile device can be configured to monitorenvironmental, system and user events. The mobile device can beconfigured to detect the occurrence of one or more events that cantrigger adjustments to system settings.

In some implementations, the mobile device can be configured to keepfrequently invoked applications up to date. The mobile device can keeptrack of when applications are invoked by the user. Based on theinvocation information, the mobile device can forecast when during theday the applications are invoked. The mobile device can thenpreemptively launch the applications and download updates so that theuser can invoke the applications and view current updated contentwithout having to wait for the application to download updated content.

In some implementations, the mobile device can receive pushnotifications associated with applications that indicate that newcontent is available for the applications to download. The mobile devicecan launch the applications associated with the push notifications inthe background and download the new content. After the content isdownloaded, the mobile device can present a graphical interfaceindicating to the user that the push notification was received. The usercan then invoke the applications and view the updated content.

In some implementations, the mobile device can be configured to performout of process downloads and/or uploads of content for applications onthe mobile device. For example, a dedicated process can be configured onthe mobile device for downloading and/or uploading content forapplications on the mobile device. The applications can be suspended orterminated while the upload/download is being performed. Theapplications can be invoked when the upload/download is complete.

In some implementations, before running an application or accessing anetwork interface, the mobile device can be configured to check batterypower and cellular data usage budgets to ensure that enough power anddata is available for user invoked operations. Before launching anapplication in the background, the mobile device can check usagestatistics to determine whether the application is likely to be invokedby a user in the near future.

Particular implementations provide at least the following advantages:Battery power can be conserved by dynamically adjusting components ofthe mobile device in response to detected events. The user experiencecan be improved by anticipating when the user will invoke applicationsand downloading content so that the user will view updated content uponinvoking an application.

Details of one or more implementations are set forth in the accompanyingdrawings and the description below. Other features, aspects, andpotential advantages will be apparent from the description and drawings,and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 illustrates a mobile device 100 configured to perform dynamicadjustment of the mobile device.

FIG. 2 illustrates an example process for invoking heuristic processes.

FIG. 3 illustrates a process for adjusting the settings of a mobiledevice using a heuristic process.

FIG. 4 illustrates an example system for performing background fetchupdating of applications.

FIG. 5 illustrates example diagrams depicting time series modeling fordetermining user invocation probabilities for applications on mobiledevice.

FIG. 6 is a flow diagram of an example process for predictivelylaunching applications to perform background updates.

FIG. 7 is a flow diagram of an example process for determining when tolaunch applications on a mobile device.

FIG. 8 is a flow diagram illustrating state transitions for an entry ina trending table.

FIG. 9 is a block diagram illustrating a system for providing pushnotifications to a mobile device.

FIG. 10 is a flow diagram of an example process for performingnon-waking pushes at a push notification server.

FIG. 11 is a flow diagram of an example process for performingbackground updating of an application in response to a low priority pushnotification.

FIG. 12 is a flow diagram of an example process for performingbackground updating of an application in response to a high prioritypush notification.

FIG. 13 is a block diagram an example system for performing backgrounddownloading and/or uploading of data on a mobile device.

FIG. 14 is flow diagram of an example process for performing backgrounddownloads and uploads.

FIG. 15 illustrates an example graphical user interface (GUI) forenabling and/or disabling background updates for applications on amobile device.

FIG. 16 is a block diagram of an example computing device that canimplement the features and processes of FIGS. 1-15.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION Overview

According to implementations, described herein is a system architecturefor enabling adaptation of a mobile device to user behavior tofacilitate tradeoffs between battery lifetime, power requirements,thermal management and performance. The system provides the underlyingevent and statistics gathering architecture and a set of heuristicprocesses that learn from a user's network conditions and applicationusage patterns over time to maximize battery life without noticeabledegradation in the user experience. This system can anticipate a user'sfuture behavior as well as the user's expectation of device performancebased on dynamically-gathered statistics and/or explicitly-specifieduser intent. The system can determine which hardware and softwarecontrol parameters to set and to what values to set the parameters inorder to improve the user experience for the anticipated user behavior.The system leverages user monitoring and hardware control to achieve anoverall improvement in the user experience while extending system andnetwork resources available to the mobile device. Thus, the system canmaximize system and network resources while minimizing the impact to theuser experience.

Data Collection—User Centric Statistics

FIG. 1 illustrates a mobile device 100 configured to perform dynamicadjustment of the mobile device 100. In some implementations, mobiledevice 100 can include a sampling daemon 102 that collects eventsrelated to device conditions, network conditions and user behavior. Forexample, sampling daemon 102 can collect statistics related toapplications, sensors and user input received by mobile device 100 andstore the statistics in event data store 104. All of the statisticsgenerated or collected can include a timestamp that indicates the timeand time zone when the statistic was generated or collected and/or ageographical location. The geographical location can be determined basedon global navigation satellite system signals, cellular transmissionsignals, Wi-Fi signals or any other location determining methodology.

In some implementations, sampling daemon 102 can receive applicationusage statistics from application manager process 106. For example,application manager 106 can be a process that starts, stops and monitorsapplications (e.g., application 108) on mobile device 100. In someimplementations, application manager 106 can report start and stop timesfor applications running on mobile device 100 to sampling daemon 102.For example, when a user or other process invokes or launches anapplication, application manager 106 can notify sampling daemon 102 ofthe application invocation. Additionally, application manager 106 canindicate to sampling daemon 102 that the application launch is initiatedin response to a push notification, user invocation or a predicted orforecasted user application invocation. When an application terminates,application manager 106 can notify sampling daemon 102 that theapplication is no longer running. The application manager 106 canprovide the name or other identifier of the application and the starttime or end time to sampling daemon 102, for example.

In some implementations, sampling daemon 102 can use the applicationstart and end notifications to generate a history of usage times perapplication. For example, the history of usage times per application caninclude for each execution of an application an amount of time that haspassed since the last execution of the application and executionduration. Sampling daemon 102 can maintain a separate history of userinvoked application launches and/or system launched applications. Thus,sampling daemon 102 can maintain usage statistics for all applicationsthat are run on mobile device 100.

In some implementations, sampling daemon 102 can receive powerstatistics from power monitor process 108. For example, power monitor108 can monitor battery capacity, discharge, usage, and chargingcharacteristics for mobile device 100. Power monitor can determine whenthe mobile device 100 is plugged into external power sources and whenthe mobile device 100 is on battery power. Power monitor 108 can notifysampling daemon 102 when the mobile device 100 is plugged into externalpower. For example, power monitor 108 can send a message to samplingdaemon 102 when power monitor detects that mobile device 100 is pluggedinto an external power source. The message can include the batterycharge at the time when the external power source is connected.

Power monitor 108 can notify sampling daemon 102 when the mobile device100 is disconnected from external power. For example, power monitor 108can send a message to sampling daemon 102 when power monitor detectsthat mobile device 100 is disconnected from an external power source.The message can include the battery charge at the time when the externalpower source is disconnected. Thus, sampling daemon 102 can maintainstatistics describing the charging distribution (e.g., charge over time)of the batteries of the mobile device 100. The charging distributionstatistics can include an amount of time since the last charge (e.g.,time since plugged into external power) and the change in battery chargeattributable to the charging (e.g., start level of charge, end level ofcharge).

In some implementations, power monitor 108 can notify sampling daemon102 of changes in battery charge throughout the day. For example, powermonitor 108 can be notified when applications start and stop and inresponse to the notifications, determine the amount of battery powerdischarged during the period and the amount of charge remaining in thebattery and transmit this information to sampling daemon 102.

In some implementations, sampling daemon 102 can receive devicetemperature statistics from thermal management process 110. For example,thermal management process 110 can monitor the operating temperatureconditions of the mobile device 100 using one or more temperaturesensors. Thermal management process 110 can be configured toperiodically report temperature changes to sampling daemon 102. Forexample, thermal management process 110 can determine the operatingtemperature of mobile device 100 every five seconds and report thetemperature to sampling daemon 102. Sampling daemon 102 can store thereported temperatures in event data store 104.

In some implementations, sampling daemon 102 can receive device settingsstatistics from device settings process 112. For example, devicesettings process 112 can be a function or process of the operatingsystem of mobile device 100. Device settings process 112 can, forexample, receive user input to adjust various device settings, such asturning on/off airplane mode, turning on/off Wi-Fi, turning on/offroaming, etc. Device settings process 112 can report changes to devicesettings to sampling daemon 102. For example, device settings process112 can notify sampling daemon 102 when the user turns on or offairplane mode on the mobile device 100. Sampling daemon 102 can generateand store statistics for the device settings based on the receivednotifications. For example, for each time a setting is enabled (ordisabled), sampling daemon 102 can store data that indicates the amountof time that has passed since the setting was previously enabled and theamount of time (e.g., duration) that the setting was enabled.

Similarly, in some implementations, sampling daemon 102 can receivenotifications from other mobile device 100 components (e.g., devicesensors 114) when other events occur. For example, sampling daemon 102can receive notifications when the mobile device's idle screen is turnedon or off, when the mobile device 100 is held next to the user's face,when a cell tower handoff is detected, when the baseband processor is ina search mode, when the mobile device 100 has detected that the user iswalking, running and/or driving. In each case, the sampling daemon 102can receive a notification at the start and end of the event. In eachcase, the sampling daemon 102 can generate and store statisticsindicating the amount of time that has passed since the event was lastdetected and the duration of the event. The sampling daemon 102 canreceive other event notifications and generate other statistics asdescribed further below with respect to specific use cases andscenarios.

Application Events

In some implementations, sampling daemon 102 can receive eventinformation from applications on mobile device 100. For example,sampling daemon 102 can receive calendar events (e.g., appointments,meetings, reminders, etc.) from calendar application 116. Samplingdaemon 102 can store the event name, event duration and/or time when theevent is scheduled to occur, for example. Sampling daemon 102 canreceive clock events from clock application 118. For example, samplingdaemon 102 can store the event name (e.g., alarm name) and/or time whenthe event is scheduled to occur. Sampling daemon 102 can receive eventinformation from other applications (e.g., media application, passbookapplication, etc.) as described further below.

Application Statistics

In some implementations, sampling daemon 102 can collect applicationstatistics across application launch events. For example, samplingdaemon 102 can collect statistics for each application across manyinvocations of the application. For example, each application can beidentified with a hash of its executable's filesystem path and theexecutable's content's hash so that different versions of the sameapplication can be handled as distinct applications.

In some implementations, sampling daemon 102 can maintain a counter thattracks background task completion assertion events for each application.For example, each time an application is run as a background task (e.g.,not visible in the foreground and/or currently in use by the user) theapplication or application manager 106 can notify sampling daemon 102when the application is terminated or is suspended and the samplingdaemon 102 can increment the counter. Sampling daemon 102 can maintain acounter that tracks the cumulative number of seconds across applicationlaunches that the application has run in the background. In someimplementations, sampling daemon 102 can maintain separate counters thatcount the number of data connections, track the amount of network datatraffic (e.g., in bytes), track the duration and size of filesystemoperations and/or track the number of threads associated with eachapplication. Sampling daemon 102 can maintain a count of the cumulativeamount of time an application remains active across applicationlaunches, for example. These are just a limited example of the types ofapplication statistics that can be tracked by sampling daemon 102. Otherstatistics can be generated or collected as described further below.

Heuristics

In some implementations, mobile device 100 can be configured withheuristic processes that can adjust settings of device components basedon events detected by sampling daemon 102. For example, heuristicprocesses 120 can include one or more processes that are configured(e.g., programmed) to adjust various system settings (e.g., CPU power,baseband processor power, display lighting, etc.) in response to one ormore trigger events and/or based on the statistics collected orgenerated by sampling daemon 102.

In some implementations, heuristic process 120 can register withsampling daemon 102 to be invoked or activated when a predefined set ofcriteria is met (e.g., the occurrence of some trigger event). Triggerevents might include the invocation of a media player application ordetecting that the user has started walking, running, driving, etc. Thetrigger event can be generalized to invoke a heuristic process 120 whensome property, data, statistic, event, etc. is detected in event data104 or by sampling daemon 102. For example, a heuristic process 120 canbe invoked when sampling daemon 102 receives an application startnotification or a temperature above a certain threshold value. Aheuristic process 120 can register to be invoked when a single eventoccurs or statistic is observed. A heuristic process 120 can register tobe invoked when a combination of events, data and/or statistics areobserved or detected. Heuristic process 120 can be triggered or invokedin response to specific user input (e.g., changing a device setting toairplane mode). When sampling process 102 detects the events for which aheuristic process 120 registered, sampling process 102 can invoke theheuristic process 120.

In some implementations, when a heuristic process 120 is invoked, theheuristic process 120 can communicate with sampling daemon 102 toretrieve data from event data 104. The heuristic process 120 can processthe event data and/or other data that the heuristic process 120 collectson its own to determine how to adjust system settings to improve theperformance of mobile device 100, improve the user's experience whileusing mobile device 100 and/or avert future problems with mobile device100.

In some implementations, heuristic process 120 can make settingsrecommendations that can cause a change in the settings of variousdevice components 122 of mobile device 100. For example, devicecomponents can include CPU, GPU, baseband processor, display, GPS,Bluetooth, Wi-Fi, vibration motor and other components.

In some implementations, heuristic process 120 can make settingsrecommendations to control multiplexer 124. For example, controlmultiplexer 124 can be a process that arbitrates between componentsettings provided by heuristic processes 120 and other processes and/orfunctions of mobile device 100 that influence or change the settings ofthe components of mobile device 100. For example, thermal managementprocess 110 can be configured to make adjustments to CPU power, displaybrightness, baseband processor power and other component settings basedon detecting that the mobile device 100 is in the middle of a thermalevent (e.g., above a threshold temperature). However, a heuristicprocess 120 can be configured to make adjustments to CPU power, displaybrightness, baseband processor power and other component settings aswell. Thus, in some implementations, heuristic process 120 and thermalmanagement process 110 can make settings adjustment recommendations tocontrol multiplexer 124 and control multiplexer 124 can determine whichsettings adjustments to make. For example, control multiplexer 124 canprioritize processes and perform adjustments based on the priority ofthe recommending process. Thus, if thermal management process 110 is ahigher priority process than heuristic process 120, control multiplexer124 can adjust the settings of the CPU, display, baseband processor,etc. according to the recommendations of thermal management process 110instead of heuristic process 120.

In some implementations, a mobile device 100 can be configured withmultiple heuristic processes 120. The heuristic processes 120 can beconfigured or reconfigured over the air. For example, the parameters(e.g., triggers, threshold values, criteria, and output) of eachheuristic process 120 can be set or adjusted over the network (e.g.,cellular data connection, Wi-Fi connection, etc.). In someimplementations, new heuristic processes 120 can be added to mobiledevice 100. For example, over time new correlations between triggerevents, statistical data and device settings can be determined by systemdevelopers. As these new correlations are identified, new heuristicprocesses 120 can be developed to adjust system settings to account forthe newly determined relationships. In some implementations, newheuristic processes 120 can be added to mobile device 100 over thenetwork. For example, the new heuristic processes 120 can be downloadedor installed on mobile device 100 over the air (e.g., cellular dataconnection, Wi-Fi connection, etc.).

Example Heuristic Processes

In some implementations, a heuristic process 120 can be configured toadjust system settings of the mobile device 100 to prevent the mobiledevice 100 from getting too hot when in the user's pocket. For example,this hot-in-pocket heuristic process can be configured to register withsampling daemon 102 to be invoked when the mobile device's display isoff and when the mobile device 100 is not playing any entertainmentmedia (e.g., music, movies, video, etc.). When invoked, thehot-in-pocket heuristic can make recommendations to reduce CPU power andGPU power, for example.

In some implementations, a heuristic process 120 can be configured toadjust location accuracy when the mobile device's display is not beingused. For example, if the mobile device's display is not being used(e.g., the display is turned off), the mobile device 100 cannot displaymap information or directions to the user. Thus, the user is not likelyusing the location services of the mobile device 100 and the locationservices (e.g., GPS location, Wi-Fi location, cellular location, etc.)can be adjusted to use less power. The location accuracy heuristicprocess can register with sampling daemon 102 to be invoked when themobile device's display is off. When invoked, the heuristic process canadjust the power levels of the GPS processor, Wi-Fi transmitter,cellular transmitter, baseband processor or terminate processes used todetermine a location of the mobile device 100.

In some implementations, a heuristic process 120 can be configured toadjust the settings of the mobile device's ambient light sensor inresponse to the user's behavior. For example, this user-adaptive ambientlight sensor (ALS) heuristic process can be invoked by sampling daemon102 when sampling daemon 102 receives data indicating that the ambientlight sensor has detected a change in the ambient light surroundingmobile device 100, that the ambient light sensor system has adjusted thebrightness of the display and/or that the user has provided input toadjust the brightness of the display.

When invoked, the user-adaptive ALS heuristic can request additionalinformation from sampling daemon 102 with respect to ALS displayadjustments and user initiated display adjustments to determine if thereis a pattern of user input that indicates that when the ALS adjusts thedisplay brightness up or down and the user adjusts the displaybrightness in the opposite direction. For example, the user may ride thebus or the train to work. The bus lights may be turned on and off duringthe ride. The ambient light sensor can detect the change in ambientlight and increase the display brightness when the lights come on. Sincethe lights only come on temporarily, the user may decrease the displaybrightness when the lights turn off again. This pattern of user inputcan be correlated to time of day, calendar or alarm entry, or travelpattern by the heuristic process to determine under what circumstancesor context the user adjusts the display brightness in response to an ALSdisplay adjustment. Once the user-adaptive ALS heuristic processdetermines the pattern of input and context, the heuristic process canadjust the settings of the ALS to be more or less aggressive. Forexample, the ALS can be adjusted to check the level of ambient lightmore or less frequently during the determined time of day, calendar oralarm entry, or travel pattern and adjust the display brightnessaccordingly.

The above heuristic processes are a few examples of heuristic processesand how they might be implemented in the system described herein. Otherheuristic processes can be implemented and added to the system as theyare developed over time. For example, additional heuristic processes canbe configured or programmed to adjust CPU, GPU, baseband processors orother components of the mobile device in response to detecting events orpatterns of events related to temperature measurements, user input,clock events (e.g., alarms), calendar events and/or other eventsoccurring and detected on the mobile device.

Example Heuristic Registration and Invocation Processes

FIG. 2 illustrates an example process 200 for invoking heuristicprocesses. At step 202, the sampling daemon 102 can be initialized. Forexample, sampling daemon 102 can be initialized during startup of themobile device 100.

At step 204, the sampling daemon 102 can invoke the heuristic processesconfigured on the mobile device 100 during initialization of thesampling daemon 102. For example, sampling daemon 102 can cause eachheuristic process 120 to execute on mobile device 100 and run throughtheir initialization subroutines.

At step 206, the sampling daemon 102 can receive event registrationmessages from each heuristic process 120. For example, during theinitialization subroutines of the heuristic processes 120, the heuristicprocesses 120 can send information to sampling daemon 102 indicatingwhich events should trigger an invocation of heuristic processes 120.Sampling daemon 102 can store the registration information in adatabase, such as event data store 104, for example. For example, theregistration information can include an identification of the heuristicprocess (e.g., executable name, file system path, etc.) and eventcriteria (identification of events, values, threshold, ranges, etc.).

At step 208, the sampling daemon 102 can receive event data. Forexample, sampling daemon 102 can receive event data from various systemcomponents, including the application manager 106, sensors 114, calendar116 and clock 118, as described above.

At step 210, the sampling daemon 102 can compare the received event datato the heuristic registration data. For example, as event data isreported to sampling daemon 102, sampling daemon 102 can compare theevent data, or the statistics generated from the event data, to theregistration information received from the heuristic processes 120.

At step 212, the sampling daemon 102 can invoke a heuristic processbased on the comparison performed at step 210. For example, if the eventdata and/or statistics, meet the criteria specified in the heuristicregistration data for a heuristic process 120, then the sampling daemon102 can invoke the heuristic process 120. For example, if the event dataand/or statistics data cross some threshold value specified for an eventby the heuristic process during registration, then the heuristic processcan be invoked by sampling daemon 102.

FIG. 3 illustrates a process 300 for adjusting the settings of a mobiledevice 100 using a heuristic process 120. At step 302, the heuristicprocess 120 is initialized. For example, the heuristic process 120 canbe invoked by sampling daemon 102 so that the heuristic process 120 canrun through its initialization subroutines. For example, the invocationcan be parameterized to indicate that the heuristic process 120 shouldrun through its initialization subroutines during this invocation.

At step 304, the heuristic process 120 can register with sampling daemon102 for system events. For example, during initialization, the heuristicprocess 120 can send a message to sampling daemon 102 that includes anidentification of events, thresholds, values or other criteria forinvoking the heuristic process 120. When the event occurs and/or thecriteria are met, sampling daemon 102 can invoke the heuristic process120.

At step 306, the heuristic process 120 can shut down or terminate. Forexample, the heuristic process 120 is not needed by the system until theregistration criteria are met for the heuristic process 120. Thus, toconserve device resources (e.g., battery power, processing power, etc.),the heuristic process 120 is terminated, shutdown or suspended until itis needed.

At step 308, the heuristic process 120 can be restarted. For example,sampling daemon 102 can invoke the heuristic process 120 when samplingdaemon 102 determines that the criteria specified by the heuristicprocess 120 in the registration message have been met.

At step 310, the heuristic process 120 can obtain event data fromsampling daemon 102. For example, once restarted, the heuristic process120 can query sampling daemon 102 for additional event data. Theheuristic process 120 can be configured to interact with other systemresources, processes, sensors, etc. to collect data, as needed.

At step 312, the heuristic process 120 can process event data todetermine component settings. For example, the heuristic process 120 canuse the event data and/or statistics from the sampling daemon 102 and/orthe data collected from other components of the system to determine howto adjust the settings of various components of the mobile device 100.

At step 314, the heuristic process 120 can transmit the determinedcomponent settings to the control multiplexer 124. For example, thecontrol multiplexer 124 can arbitrate device settings recommendationsreceived from the heuristic process 120 and other system components(e.g., thermal management process 110). The control multiplexer 124 canthen adjust various components (e.g., CPU, GPU, baseband processor,display, etc.) of the mobile device 100 according to the receivedsettings recommendations.

Keep Applications Up to Date—Fetching Updates

FIG. 4 illustrates an example system 400 for performing background fetchupdating of applications. In some implementations, mobile device 100 canbe configured to predictively launch applications as backgroundprocesses of the mobile device 100 so that the applications can downloadcontent and update their interfaces in anticipation of a user invokingthe applications. For example, the user application launch history datamaintained by sampling daemon 102 can be used to forecast when the userwill invoke applications of the mobile device 100. These applicationscan be launched by the application manager 106 prior to user invocationso that the user will not be required to wait for a user invokedapplication to download current content and update the graphicalinterfaces of the applications.

Determining when to Launch Applications

In some implementations, application manager 106 can request anapplication invocation forecast from sampling daemon 102. For example,sampling daemon 102 can provide an interface that allows the applicationmanager 106 to request information that indicate when to launchapplications of the mobile device 100. Sampling daemon 102 can maintainstatistics that indicate when the user invokes applications on themobile device 100, as described above. When application manager 106calls the “when to launch” interface, sampling daemon 102 can processthe user application invocation statistics to determine when during theday each application is typically invoked by the user. For example,sampling daemon 102 can calculate a probability that a particular timeof day or time period will include an application invocation by a user.

In some implementations, application manager 106 can invoke the “when tolaunch” interface of sampling daemon 102 during initialization of theapplication manager 106. For example, application manager 106 can beinvoked or launched during startup of mobile device 100. Whileapplication manager 106 is initializing, application manager 106 canrequest a forecast of application invocations for the next 24 hours.Once the initial 24 hour period has passed, application manager 106 canrequest another 24 hour forecast. This 24 forecast cycle can continueuntil the mobile device 100 is turned off, for example.

In some implementations, sampling daemon 102 can generate an applicationinvocation forecast for a 24 hour period. For example, sampling daemon102 can divide the 24 hour period into 96 fifteen minute timeslots.Sampling daemon 102 can determine which applications have been invokedand at what time the applications were invoked over a number (e.g., 1 to7) of previous days of operation based on the application launch historydata collected by sampling daemon 102 and stored in event data store104. In some implementations, sampling daemon 102 will exclude anapplication from the invocation forecast when background updates havebeen disabled for the application.

In some implementations, each 15 minute timeslot can be ranked accordingto a probability that an (e.g., any) application will be invoked in the15 minute timeslot. For example, if the sampling daemon 102 is using theprevious seven days of user invoked application launch history data todetermine the probabilities for the 15 minute timeslots, sampling daemon102 can calculate how many user invoked application launches occurredover the previous seven days (e.g., total app launches) and determinehow many application launches occurred within each 15 minute timeslot(e.g., n timeslot). For example, if a 15 minute window corresponds tothe time period 12:00 pm-12:15 pm, then the number of applicationslaunched within the 15 minute window will include all user initiatedapplication launches occurring from 12:00 pm-12:15 pm on each of thelast seven days. Sampling daemon 102 can then determine the probabilityof an application being invoked by a user within a given 15 minutetimeslot by dividing the number of application launches occurring withina given 15 minute window of each of the seven days by the totalapplication launches over the seven day period (e.g., n timeslot/totalapp launches).

Once the application invocation probabilities for each of the 96timeslots is calculated, sampling daemon 102 will select a number (e.g.,up to 64) of the timeslots having the largest non-zero probabilities andreturn information identifying the timeslots to application manager 106.For example, sampling daemon 102 can send application manager 106 a listof times (e.g., 12:00 pm, 1:45 pm, etc.) that correspond to the start of15 minute timeslots that correspond to probable user invoked applicationlaunches.

In some implementations, each of the 96 timeslots can be ranked based onrecurring application invocations within each respective timeslot. Forexample, a timeslot can be highly ranked if a user invokes the sameapplication in the same timeslot during each day over the last number(e.g., seven) of days. A timeslot can be lowly ranked if a user invokeddifferent applications (e.g., the same application is not invoked morethan once) in the same timeslot during each day over the last number ofdays. For example, if during a timeslot (e.g., 12:00-12:15 pm) for thelast seven days, application ‘A’ is invoked by the user, the timeslotcan have a ranking or a score based on the ratio of days the applicationis invoked over the total number of days considered (e.g., 7/7=1). Ifduring a timeslot (e.g., 12:00-12:15 pm) for the last seven days,application ‘B’ is invoked by the user on only one day, then thetimeslot can have a ranking or score based on the ratio of days theapplication is invoked over the total number of days considered (e.g.,1/7=0.14). If application A and application B are invoked in the12:00-12:15 pm timeslot over the seven day period, then the timeslot canbe ranked or scored according to the highest score generated. Forexample, the score for the timeslot using application A is 1.0, thescore for the timeslot using application B is 0.14, thus, the score forthe timeslot is 1.0. Timeslots having no application invocations can beassigned a score of zero.

In some implementations, sampling daemon 102 can select a number (e.g.,64) of timeslots having the highest score and send them to applicationmanager 106. For example, sampling daemon 102 can send applicationmanager 106 a list of times (e.g., 12:00 pm, 1:45 pm, etc.) thatcorrespond to the start of 15 minute timeslots that correspond toprobable user invoked application launches.

In some implementations, application manager 106 can set timers based onthe timeslots provided by sampling daemon 102. For example, applicationmanager 106 can create or set one or more timers (e.g., alarms) thatcorrespond to the timeslots identified by sampling daemon 102. When eachtimer goes off (e.g., at 12:00 pm), application manager 106 can wake(e.g., if sleeping, suspended, etc.) and determine which applicationsshould be launched for the current 15 minute timeslot. Thus, the timerscan trigger a fetch background update for applications that are likelyto be invoked by a user within the corresponding timeslot.

In some implementations, other events can trigger a fetch backgroundupdate for applications. For example, turning on a cellular radio,baseband processor or establishing a network connection (e.g., cellularor Wi-Fi) can trigger a background application launch so that theapplication update can take advantage of an active network connection.Unlocking the mobile device 100, turning on the display and/or otherinteractions can trigger a background application launch and fetchupdate, as described further below. In some implementations, applicationmanager 106 will not trigger a background application launch and fetchupdate if any background updates were Performed within a Previous Number(e.g., Seven) of Minutes.

Determining What Applications to Launch

In some implementations, application manager 106 can request thatsampling daemon 102 provide a list of applications to launch for thecurrent times. For example, when a timer goes off (e.g., expires) for a15 minute timeslot, application manager can call a “what to launch”interface of sampling daemon 102 so that sampling daemon 102 candetermine which applications to launch for the current timeslot.Sampling daemon 102 can then generate a list of applications andcorresponding scores indicating the probability that each applicationwill be invoked by the user at about the current time, as describedfurther below. In some implementations, sampling daemon 102 will excludean application from the list of applications when background updateshave been disabled for the application.

In some implementations, sampling daemon 102 can determine theprobability that each application will be invoked by a user for acurrent (e.g., 15 minute) timeslot. For example, in response to aninvocation of the “what to launch” interface, sampling daemon 102 candetermine the likelihood that each application will be invoked by theuser.

FIG. 5 illustrates example diagrams 500, 530 and 560 depicting timeseries modeling for determining user invocation probabilities forapplications on mobile device 100. In some implementations, samplingdaemon 102 can use time series modeling to determine the user invocationprobabilities for each application on mobile device 100. If anapplication does not show up in the time series, the application can beassigned a zero probability value.

In some implementations, user invocation probabilities can be generatedbased on recent application invocations. For example, user invocationprobabilities can be generated using application launch data for theprevious two hours (e.g., user initiated application launches within thelast two hours). As illustrated by diagram 500, application launchhistory data can indicate a number (e.g., four) of applications werelaunched in the previous two hours. For example, the dots and circlescan represent applications where the empty circles can represent asingle particular application (e.g., email, social networkingapplication. etc.). The probability associated with the particularapplication using recent history can be calculated by dividing thenumber of invocations of the particular application (e.g., 2) by thetotal number of application invocations (e.g., 4) within the previoustwo hours. In the illustrated case, the probability associated with theparticular application using recent application launch history data is2/4 or 50%.

User invocation probabilities can be generated based on a daily historyof application launches (e.g., which applications were launched at thecurrent time +−2 hours for each of the previous seven days). Diagram 530represents using a daily history to determine a user invocationprobability for an application. For example, each box of diagram 530represents time windows (e.g., current time +−2 hours) in each of anumber (e.g., 7) of previous days that can be analyzed to determine theuser invocation probability for a particular application (e.g., emptycircle). The probability associated with the particular applicationusing daily history data can be calculated by dividing the number ofinvocations of the particular application in all windows (e.g., 6) bythe total number of application invocations in all windows (e.g., 22).In the illustrated case, the probability associated with the particularapplication using daily launch history data is 6/22 or 27%.

User invocation probabilities can be generated based on a weekly historyof application launches (e.g., which applications were launched at thecurrent time +−2 hours seven days ago). Diagram 560 represents using aweekly history to determine a user invocation probability for anapplication. For example, if the current day and time is Wednesday at 1pm, the user invocation probability for an application can be based onapplications launched during the previous Wednesday during a time windowat or around 1 pm (e.g., +−2 hours). In the illustrated case, theprobability associated with the particular application (e.g., emptycircle) using weekly application launch history data is ¼ or 25%.

In some implementations, the recent, daily and weekly user invocationprobabilities can be combined to generate a score for each application.For example, the recent, daily and weekly probabilities can be combinedby calculating a weighted average of the recent (r), daily (d) andweekly (w) probabilities. Each probability can have an associated weightand each weight can correspond to an empirically determined predefinedimportance of each probability. The sum of all weights can equal one.For example, the weight for probability based on recent launches can be0.6, the weight for the daily probability can be 0.3, and the weight forthe weekly probability can be 0.1. Thus, the combined probability scorecan be the sum of 0.6(r), 0.3(d) and 0.1(w) (e.g.,score=0.6r+0.3d+0.1w).

Referring back to FIG. 4, once the probability score is determined foreach application based on the recent, daily and weekly probabilities,the sampling daemon 102 can recommend a configurable number (e.g.,three) of applications having the highest non-zero probability scores tothe application manager 106 for launching to perform background fetchdownloads/updates.

In some implementations, sampling daemon 102 can exclude from the “whatto launch” analysis described above applications that do not supportbackground updates (e.g., fetching) application updates, applicationswhere the user has turned off background updates, applications that haveopted out of background updates, and/or whichever application iscurrently being used by the user or is in the foreground on the displayof the mobile device 100 since it is likely that the foregroundapplication is already up to date.

Determining that it is Ok to Launch an Application

In some implementations, when application manager 106 receives the listof applications to launch and application scores, application manager106 can call an “ok to launch” interface of sampling daemon 102 todetermine if it is ok to launch each application. For example, samplingdaemon 102 can analyze network conditions, device conditions,environmental conditions, data and energy budgets and other data todetermine if it is ok for application manager 106 to launch a particularapplication. Application manager 106 can send sampling daemon 102 anapplication identifier when calling the “ok to launch” interface, forexample.

In some implementations, other applications on mobile device 102 cancall the “ok to launch” interface of sampling daemon 102 to determinewhether it is ok to launch an application in the background of mobiledevice 100. For example, the push service daemon described below caninvoke the “ok to launch” interface to determine if it is ok to launchapplications in response to receiving a push notification. In someimplementations, sampling daemon 102 will return a “no” reply value whenbackground updates have been disabled for an application identified inan “ok to launch” request.

Environmental Conditions

In some implementations, sampling daemon 102 can determine whether toallow launching the identified application based on the environmentalconditions of the mobile device 100. For example, environmentalconditions can include the current state of the mobile device 100, thestate of network connections and/or other conditions as described below.In some implementations, when the “ok to launch” interface is called byapplication manager 106 (or another application, process or daemon),sampling daemon 102 can return values indicating that it is “never” okto launch the identified application, “no” it is not ok to launch theapplication, or “yes” it is ok to launch the application. For example, a“yes” value will be returned unless one of the conditions belowindicates that the application should not be launched. Sampling daemon102 will return a “never” value when the identified application has notbeen recently used (e.g., not used in the past 8 weeks), when the userhas disabled the application and/or when the application was explicitlyclosed by the user.

In some implementations, sampling daemon 102 can indicate thatapplication manager 106 should not launch an application when the mobiledevice 100 is connected to a voice call and not connected to a Wi-Finetwork connection. For example, to prevent background updatingprocesses (e.g., fetch processes) from interfering with or reducing thequality of voice calls, the sampling daemon 102 will not allowapplication manager 106 to launch a background updating process when theuser is connected to a voice call and not connected to a Wi-Ficonnection. Thus, sampling daemon 102 will return a “no” value inresponse to an “ok to launch” request when the mobile device 100 isconnected to a call and not connected to Wi-Fi.

In some implementations, sampling daemon 102 can indicate thatapplication manager 106 should not launch an application when the mobiledevice 100 has detected a thermal event. For example, the thermalmanagement process 110 can monitor the temperature of the mobile device100 and report temperature values to sampling daemon 102. When samplingdaemon 102 determines that the temperature of mobile device 100 is abovea threshold temperature value, sampling daemon 102 can preventapplication manager 106 from launching additional applications that mayincrease the operating temperature of mobile device 100 further byreturning a “no” value when application manager makes an “ok to launch”request.

In some implementations, sampling daemon 102 can indicate thatapplication manager 106 should not launch an application when the mobiledevice 100 has a poor quality cellular network connection. A poorquality cellular connection can be determined when transfer rate and/orthroughput are below predefined threshold values. For example, if themobile device 100 has a poor quality cellular network connection and isnot connected to Wi-Fi, the sampling daemon 102 can prevent applicationmanager 106 from launching an application that will waste battery energyand cellular data by attempting to download or upload data over a poorcellular connection by returning a “no” value when application managermakes an “ok to launch” request.

In some implementations, sampling daemon 102 can indicate thatapplication manager 106 should not launch an application when mobiledevice 100 is using more than a threshold amount (e.g., 90%) of memoryresources. For example, if mobile device 100 is already running manyapplications or processes that are using most of the memory resources ofthe mobile device 100, launching additional applications in thebackground will only reduce the performance of the mobile device 100 byusing up remaining memory resources. Thus, when sampling daemon 102determines that memory usage exceeds a threshold value (e.g., 75%),sampling daemon 102 can prevent application manager 106 from launchingadditional applications by returning a “no” value when applicationmanager makes an “ok to launch” request.

In some implementations, sampling daemon 102 can indicate thatapplication manager 106 should not launch an application when anapplication has opted out of background updates or a user has turned offbackground updates for an application. For example, an application canprogrammatically (e.g., dynamically) determine (based on programmerdefined criteria) that the application should opt out of backgroundupdates for a period of time. Alternatively, a user can interact with asettings user interface to turn off background updates for anapplication. In either case, sampling daemon 102 can determine thatbackground updates have been disabled for the application and preventapplication manager 106 from launching the application by returning a“no” value when application manager 106 makes an “ok to launch” requestfor an application.

Accounting for Budgets and Rate Limits

In some implementations, sampling daemon 102 can determine whether it isok to launch an application based on an energy budget, a data budgetand/or application launch rate limits configured for mobile device 100.Sampling daemon 102 can store budget and rate limit information inaccounting data store 402, including counters for keeping track ofremaining data and energy budgets for the current time period (e.g.,current hour).

Energy Budget

In some implementations, sampling daemon 102 can determine whether it isok to launch an application based on an energy budget. For example, theenergy budget can be a percentage (e.g., 5%) of the capacity of themobile device's battery in milliamp hours. The energy budget can bedivided between predictive fetch applications (e.g., 2%), as describedabove, and push applications and background download/upload (e.g., 3%),as described below.

In some implementations, the energy budgets can be distributed amongeach hour in a 24 hour period. For example, sampling daemon 102 canutilize the battery charging statistics collected and stored in eventdata store 104 to determine a distribution that reflects a typicalhistorical battery usage for each hour in the 24 hour period. Forexample, each hour can be assigned a percentage of the energy budgetbased on the historically or statistically determined energy usedistribution or application usage forecast, as described above. Eachhour will have at least a minimum amount of energy budget that isgreater than zero (e.g., 0.1%, 1%, etc.). For example, 10% of the energybudget can be distributed among hours with no use data and the remaining90% of the energy budget can be distributed among active use hoursaccording to historical energy or application use. As each hour passes,the current energy budget will be replenished with the energy budget forthe new/current hour. Any energy budget left over from a previous hourwill be added to the current hour's budget.

In some implementations, accounting data store 402 can include a counterfor determining how much energy budget remains for fetch applications(e.g., predictively launched applications). For example, accounting datastore 402 can include one or more counters that are initialized with theenergy budgets (e.g., fetch budget, push and background download/upload)for the current hour. When the energy budget is used by an application,the corresponding (e.g., fetch or push) energy budget can be decrementedby a corresponding amount. For example, application manager 106 cannotify sampling daemon 102 when an application is launched orterminated. In turn, sampling daemon 102 can notify power monitor 108when an application is launched and when the application is terminated.Based on the start and stop times, power monitor 108 can determine howmuch energy was used by the application. Power monitor 108 can transmitthe amount of power used by the application to sampling daemon 102 andsampling daemon 102 can decrement the appropriate counter by the amountof power used.

In some implementations, when no energy budget remains for the currenthour, sampling daemon 102 can respond with a “no” reply to an ok tolaunch request. For example, when the energy budget counters inaccounting data store 402 are decremented to zero, no energy budgetremains and no additional background applications will be launched.

In some implementations, sampling daemon 102 will not base an “ok tolaunch” determination on the energy budget when the mobile device 100 isplugged into external power. For example, a remaining energy budget ofzero will not prevent applications from launching when the mobile device100 is plugged into an external power source.

Data Budget

In some implementations, sampling daemon 102 can determine whether it isok to launch an application based on a data budget. For example,sampling daemon 102 can determine an average amount of network dataconsumed by the mobile device 100 based on statistical data collected bysampling daemon 102 and stored in event data store 104. The network databudgets (e.g., fetch/push budget, background download/upload budget) canbe calculated as a percentage of average daily network data consumed bythe user/mobile device 100. Alternatively, the network data budgets canbe predefined or configurable values (e.g., 15 MB per day for fetch/pushbudget, 5 MB per day for background download/upload).

In some implementations, the network data budgets can be distributedamong each hour in a 24 hour period. For example, each hour can beallocated a minimum budget (e.g., 0.2 MB). The remaining amount of thenetwork data budget can be distributed among each of the 24 hoursaccording to historical network data use. For example, sampling daemon102 can determine based on historical statistical data how much networkdata is consumed in each hour of the day and assign percentagesaccording to the amounts of data consumed in each hour. As each hourpasses, the current data budget will be replenished with the data budgetfor the new/current hour. Any data budget left over from a previous hourwill be added to the current hour's data budget.

In some implementations, accounting data store 402 can maintain datacounters for network data budgets. For example, accounting data store402 can maintain a data counter for fetch/push applications. Accountingdata store 402 can maintain a data counter for backgrounddownload/upload operations. As network data is consumed, the datacounters can be decremented according to the amount of network dataconsumed. For example, the amount of network data consumed can bedetermined based on application start and stop times provided tosampling daemon 102 by application manager 106. Alternatively, theamount of network data consumed can be provided by the process utilizingthe network interface (e.g., the background download/upload daemondescribed below).

In some implementations, sampling daemon 102 can keep track of whichnetwork interface (e.g., cellular or Wi-Fi) is used to consume networkdata and determine the amount of network data consumed based on thenetwork interface. The amount of network data consumed can be adjustedaccording to weights or coefficients assigned to each interface. Forexample, network data consumed on a cellular data interface can beassigned a coefficient of one (1). Network data consumed on a Wi-Fiinterface can be assigned a coefficient of one tenth (0.1). The totalnetwork data consumed can be calculated by adding the cellular dataconsumed to Wi-Fi data consumed divided by ten (e.g., totaldata=1*cellular data+0.1*Wi-Fi). Thus, data consumed over Wi-Fi willimpact the data budget much less than data consumed over a cellular dataconnection.

In some implementations, when no data budget remains for the currenthour, sampling daemon 102 can respond with a “no” reply to an ok tolaunch request. For example, when the data budget counters in accountingdata store 402 are decremented to zero, no data budget remains and noadditional background applications will be launched.

Global Application Launch Rate Limit

In some implementations, sampling daemon 102 can determine whether it isok to launch an application based on a global application launch ratelimit. For example, sampling daemon 102 can be configured with a numberof background applications (e.g., fetch and/or push backgroundapplications) that application manager 106 can launch per hour. In someimplementations, launch rate limits will only be considered for pushnotification triggered application launches, as described below. Forexample, application manager 106 can be limited to launching 64background applications per hour. Sampling daemon 102 can maintain acounter that tracks the number of background application launches thathave been performed in the current hour. Each hour the globalapplication launch counter can be reset to allow more applicationlaunches. However, if the global application launch rate for the currenthour is exceeded, then no additional background applications can belaunched and sampling daemon 102 will return a “no” reply to an ok tolaunch request.

Per Application Launch Rate Limit

In some implementations, sampling daemon 102 can determine whether it isok to launch an application based on an individual application launchrate limit. For example, sampling daemon 102 can be configured with anumber times that individual background applications (e.g., fetch and/orpush background applications) can be launched per hour. For example,application manager 106 can be limited to launching the same application15 times per hour. Sampling daemon 102 can maintain a counter thattracks the number of times individual applications are launched in thebackground per hour. Each hour the individual application launch countercan be reset to allow more application launches. However, if theindividual application launch rate for the current hour is exceeded fora particular application, then the particular application cannot belaunched again in the current hour and sampling daemon 102 will return a“no” reply to an ok to launch request that identifies the particularapplication.

Launching a Background Fetch Application

In some implementations, when application manager 106 makes an “ok tolaunch” call to sampling daemon 102 and receives a “yes” reply,application manager 106 can invoke or launch the identified application(e.g., application 108) in the background of the operating environmentof mobile device 100. For example, the application 108 can be launchedin the background such that it is not apparent to the user thatapplication 108 was launched. The application 108 can then communicateover a network (e.g., the internet) with content server 404 to downloadupdated content for display to the user. Thus, when the usersubsequently invokes application 108 (e.g., brings the application tothe foreground), the user will be presented with current and up-to-datecontent without having to wait for application 108 to download thecontent and refresh the application's user interfaces.

In some implementations, application manager 106 can be configured tolaunch background fetch enabled applications when the mobile device 100is charging and connected to Wi-Fi. For example, sampling daemon 102 candetermine when mobile device 100 is connected to an external powersource and connected to the network (e.g., internet) over Wi-Fi and senda signal to application manager 106 to cause application manager 106 tolaunch fetch enabled applications that have been used within a previousamount of time (e.g., seven days).

Example Background Fetch Processes

FIG. 6 is a flow diagram of an example process 600 for predictivelylaunching applications to perform background updates. For example,process 600 can be performed by application manager 106 to determinewhen to launch background applications configured to fetch data updatesfrom network resources, such as content server 404 of FIG. 4. Additionaldescription related to the steps of process 600 can be found withreference to FIG. 4 above.

At step 602, application manager 106 can receive an applicationinvocation forecast from sampling daemon 102. For example, applicationmanager 106 can be launched during startup of mobile device 100. Duringits initialization, application manager 106 can request a forecast ofapplications likely to be invoked by a user of the mobile device 100over the next 24 hour period. This forecast can indicate when to launchapplications, for example. The 24 hour period can be divided into 15minute blocks and each 15 minute block can be associated with aprobability that the user will invoke an application during the 15minute block. The forecast returned to application manager 106 canidentify up to 64 15 minute blocks of time when the user is likely toinvoke an application.

At step 604, application manager 106 can set timers based on theapplication launch forecast. For example, application manager 106 canset a timer or alarm for each of the 15 minute blocks identified in theapplication launch forecast returned to the application manager 106 bysampling daemon 102.

At step 606, application manager 106 can request sampling daemon 102identify what applications to launch. For example, when a timer expiresor alarm goes off, application manager can wake, if sleeping orsuspended, and request from sampling daemon 102 a list of applicationsto launch for the current 15 minute block of time. Sampling daemon 102can return a list of applications that should be launched in thebackground on mobile device 100.

At step 607, application manager 106 can send a request to samplingdaemon 102 asking if it is ok to launch an application. For example, foreach application identified by sampling daemon 102 in response to the“what to launch” request, application manager 106 can ask samplingdaemon 102 whether it is ok to launch the application. Sampling daemon102 can return “yes” if it is ok to launch the application, “no” if itis not ok to launch the application or “never” if it is never ok tolaunch the application.

At step 610, application manager 106 can launch an application. Forexample, if sampling daemon 102 returns an “ok” response for the “ok tolaunch” request, application manager 106 will launch the application asa background process of mobile device 100. If sampling daemon 102returns a “no” or “never” response to the “ok to launch” request,application manager 106 will not launch the application.

At step 612, application manager 106 can transmit an application launchnotification to sampling daemon 102. For example, sampling daemon 102can use the application launch notification to generate applicationlaunch statistics, data usage statistics, energy use statistics and/orother application related statistics as needed.

At step 614, application manager 106 can detect that the launchedapplication has terminated. For example, application manager 106 candetermine when the launched application is no longer running on mobiledevice 100.

At step 616, application manager 106 can transmit an applicationtermination notification to sampling daemon 102. For example, samplingdaemon 102 can use the application termination notification to generateapplication launch statistics, data usage statistics, energy usestatistics and/or other application related statistics as needed.

FIG. 7 is a flow diagram of an example process 700 for determining whento launch applications on a mobile device 100. For example, process 700can be used to determine when to launch applications, what applicationsshould be launched and if it is ok to launch applications based onapplication use statistics, data and energy budgets and mobile deviceconditions, as described above in detail with reference to FIG. 4

At step 702, sampling daemon 102 can receive an application launchforecast request from application manager 106. For example, applicationmanager 106 can request an application launch forecast for the next 24hours. Once the 24 hour period has passed, application manager 106 canrequest an application launch forecast for the subsequent 24 hourperiod. For example, application manager 106 can request an applicationlaunch forecast every 24 hours.

At step 704, sampling daemon 102 can determine an application launchforecast. For example, the application launch forecast be used topredict when user initiated application launches are likely to occurduring a 24 hour period. For example, sampling daemon 102 can determinean application launch forecast for a 24 hour period. The 24 hour periodcan be divided into 15 minute time blocks. For each 15 minute time block(e.g., there are 96 15 minute time blocks in a 24 hour period), samplingdaemon 102 can use historical user invocation statistics determine aprobability that a user initiated application launch will occur in the15 minute time block, as described above with reference to FIG. 4.

At step 706, sampling daemon 102 can transmit the application launchforecast to application manager 106. For example, sampling daemon 102can select up to 64 15 minute blocks having the highest non-zeroprobability of a user initiated application launch. Each of the selected15 minute blocks can be identified by a start time for the 15 minuteblock (e.g., 12:45 pm). Sampling daemon 102 can send the list of 15minute block identifiers to application manager 106 as the applicationlaunch forecast.

At step 708, sampling daemon 102 can receive a request for whatapplications to launch at a current time. For example, applicationmanager 106 can send a request to sampling daemon 102 for samplingdaemon 102 to determine which applications should be launched at oraround the current time.

At step 710, sampling daemon 102 can score applications for the currenttime based on historical user data. Sampling daemon 102 can determinewhich applications that the user is likely to launch in the near futurebased on historical user initiated application launch data collected bysampling daemon 102. Sampling daemon 102 can utilize recent applicationlaunch data, daily application launch data and/or weekly applicationlaunch data to score applications based on the historical likelihoodthat the user will invoke the application at or around the current time,as described above with reference to FIG. 4 and FIG. 5.

At step 712, sampling daemon 102 can transmit the applications andapplication scores to application manager 106. For example, samplingdaemon 102 can select a number (e.g., three) of applications having thehighest scores (e.g., highest probability of being invoked by the user)to transmit to application manager 106. Sampling daemon 102 can excludeapplications that have been launched within a previous period of time(e.g., the previous 5 minutes). Sampling daemon 102 can transmitinformation that identifies the highest scored applications and theirrespective scores to application manager 106, as described above withreference to FIG. 4.

At step 714, sampling daemon 102 can receive a request from applicationmanager 106 to determine whether it is ok to launch an application. Forexample, sampling daemon 102 can receive an “ok to launch” request thatidentifies an application.

At step 716, sampling daemon 102 can determine that current mobiledevice conditions and budgets allow for an application launch. Forexample, sampling daemon 102 can analyze the environmental conditions ofthe mobile device 100, data and energy budgets, application launch ratelimits, network conditions and other data to determine if the currenttime is a good time to launch an application, as described in detailabove with reference to FIG. 4.

At step 718, sampling daemon 102 can transmit a reply to applicationmanger 106 indicating that it is ok to launch the identifiedapplication. For example, if conditions are good for a backgroundapplication launch, sampling daemon 102 can return a “yes” value toapplication manager 106 so that application manager 106 can launch theidentified application.

Short Term Trending

In some implementations, sampling daemon 102 can be configured to detectwhen applications are trending and predictively launch the applicationsin the background on mobile device 100 based on the detecting trend. Forexample, an application is trending if the application is beingrepeatedly invoked by a user of mobile device 100. In some cases, thetrending application is a new application or, prior to the trend, ararely used application that may not be included in the “what to launch”application forecasting described above. Thus, the trending applicationmay not be kept up to date using the application launch forecastingmethods described above.

The purpose of application launch trend detection is to detectapplications which are being launched repeatedly by the user and todetermine an approximate cadence (e.g., periodicity) with which theapplications are being launched, erring on reporting a smaller cadence.Applications that are being invoked repeatedly by a user are said to be“trending.” The determined cadence can then be used by applicationmanager 106 to set timers that will trigger the application manager 106to launch the trending applications in the background so that theapplications will be updated when the user invokes the applications, asdescribed above. For example, if the cadence is 5 minutes for anapplication, application manager 106 can set a timer that will expireevery 4 minutes and cause application manager 106 to launch theapplication so that the application can receive updated content andupdate the application's interfaces before being invoked again by theuser. In some implementations, the trend detection mechanisms describedherein can be used to detect other system event trends beyondapplication launches, such as repeated software or networknotifications, application crashes, etc.

In some implementations, sampling daemon 102 can maintain a trendingtable that can be used to track the behavior of a number ofapplications. The trending table can include an applicationidentification field (APPID), a state field (STATE), a last launchtimestamp (LLT), an inter-launch cadence (ILC) that indicates the amountof time between launches, and a confidence field (C).

FIG. 8 is a flow diagram 800 illustrating state transitions for an entry(e.g., application) in the trending table. Initially at step 802, thetrending table can include empty entries (e.g., records) where theAPPID, LLT, ILC and C fields are empty (e.g., N/A) and the STATE is setto “invalid” (I). When an application is launched at time t, thetrending table is scanned for an available entry (e.g., an entry instate I). Among the possible invalid entries, several methods can beused for selecting an entry to use. For example, a random invalid entrycan be selected. Alternatively, an invalid entry can be selected suchthat all the empty entries in the trending table are kept in consecutiveorder. If no invalid entry exists, the oldest entry (or a random entry)in transient (T) state can be selected to track the newly launchedapplication. If no I or T state entries exist, the oldest new (N) stateentry can be selected to track the newly launched application.

At step 804, once the trending table entry is selected, the STATE fieldof the selected entry for tracking the newly launched application can beset to new (N), the APPID can be set to an identifier for the newlylaunched application, the LLT field can be set to the current time t(e.g., wall clock time) and the ILC and C fields are set to predefinedminimum values ILC_MIN (e.g., 1 minute) and C_MIN (e.g., zero).

At step 806, on the next launch of the same application at time t″, theentry in the table for the application is found, if it still exists andhas not been evicted (e.g., selected to track another application). TheSTATE of the entry is set to transient (T), the ILC is set to thedifference between the LLT and the current system time (e.g., t′-t ort′-LLT), and the C field is incremented (e.g., by predefined valueC_DELTA). Alternatively, the ILC field can be set to some other functionof its old and new values, such as the running average.

At step 808, on the next launch of the same application at time t″, theentry in the table for the application is found, if it still exists andhas not been evicted (e.g., selected to track another application). TheSTATE of the entry can remain set to transient (T), the ILC is set tothe difference between the LLT and the current wall clock time (e.g.,t″-t′ or t″-LLT), and the C field is incremented again (e.g., bypredefined value C_DELTA).

At step 810, if, after several launches of the application, the C valueof the trending table entry reaches (e.g., equals) a threshold value(e.g., C_HIGHTHRESHOLD), at step 811, the state of the application entrycan be changed to STATE=A. If, at step 810, the C value of the trendingtable entry does not reach the threshold value (e.g., C_HIGHTHRESHOLD),the values of the entry can be updated according to step 808.

Whenever the application is launched while in state “A”, if the timebetween the last launch and the time of launch is within some amount oftime (e.g., ILC_EPSILON=5 minutes), then the application entry'sconfidence (C) field is incremented until it reaches a predefinedmaximum value (e.g., C_MAX). When an application entry in the trendingtable is in the active (A) state, the entry's ILC value can be used asan estimation of the rate of launch (e.g., cadence) and the entry'sAPPID can be used to identify the trending application.

In some implementations, sampling daemon 102 can send the applicationidentifier (APPID) and cadence value (ILC) to application manager 106 sothat application manager 106 can launch the identified application inthe background in anticipation of a user invocation of the applicationso that the application can receive updated content prior the userlaunching the application, as described above. For example, applicationmanager 106 can start a timer based on the cadence value that will wakethe application manager 106 to launch the application in anticipation ofa user invoking the application.

In some implementations, sampling daemon 102 can send applicationmanager 106 a signal or notification indicating that a trendingapplication should be launched by application manager 106. For example,application manager 106 can register interest in an application bysending sampling daemon 102 an application identifier. Sampling daemon102 can monitor the application for user invocation to determine whetherthe application is trending, as described above. If the application istrending, sampling daemon 102 can determine the cadence of invocation,as described above, and send a notification or signal to applicationmanager 106 at a time determined based on the cadence. For example, ifthe cadence is four minutes, sampling daemon 102 can send a signal toapplication manager 106 every 3 minutes to cause application manager 106to launch the application. If the cadence changes to six minutes,sampling daemon 102 can detect the cadence change and adjust whenapplication manager 106 is signaled. For example, sampling daemon 102can signal application manager 106 to launch the application every 5minutes instead of every 3 minutes to adjust for the decreased cadence(e.g., increased time period between invocations).

At each inspection of the trending table for any reason (e.g., adding anew entry, updating an existing entry, etc.), all entries in STATE=T orSTATE=A whose time since last launch is greater than their ILC byILC_EPSILON will have their C values decremented. Any entry whose Cvalue at that point falls below a minimum threshold value (e.g.,C_LOWTHRESHOLD) is demoted. An entry can be demoted from state A tostate T or from state T to state I, for example.

In some implementations, the trend detection mechanism described abovecan be used to detect trending events other than application invocationsor launches. For example, the trend detection method and trending tabledescribed above can be used to detect and track any recurring event onmobile device 100. A trending event can include screen touches, networkconnections, application failures, the occurrence of network intrusionsand/or any other event that can be reported or signaled to samplingdaemon 102.

Push Notifications

FIG. 9 is a block diagram 900 illustrating a system for providing pushnotifications to a mobile device 100. In some implementations, mobiledevice 100 can be configured to receive push notifications. For example,a push notification can be a message that is initiated by a pushprovider 902 and sent to a push service daemon 904 running on mobiledevice 100 through push notification server 906.

In some implementations, push provider 902 can receive authorization tosend push notifications to mobile device 100 through a userauthorization request presented to a user of mobile device 100 byapplication 908. For example, push provider 902 can be a server owned,operated and/or maintained by the same vendor that created (e.g.,programmed, developed) application 908. Push provider 902 can receiveauthorization from a user to send push notifications to mobile device100 (e.g., push service daemon 904) when application 908 presents a userinterface on mobile device 100 requesting authorization for pushprovider 902 to send push notifications to mobile device 100 and theuser indicates that push notifications are authorized. For example, theuser can select a button on the user interface presented by application908 to indicate that push notifications are authorized for the pushprovider 902 and/or application 908. Push provider 902 can then receivea device token that identifies mobile device 100 and that can be used toroute push notifications to mobile device 100. For example, pushnotification server 906 can receive a device token with a pushnotification and use the device token to determine which mobile device100 should receive the push notification.

In some implementations, mobile device 100 can send informationidentifying authorized push applications to push notification server906. For example, mobile device 100 can send a message 926 containingpush notification filters 914 and the device token for mobile device 100to push notification server 906. Push notification server 906 can storea mapping of device tokens (e.g., identifier for mobile device 100) topush filters 914 for each mobile device serviced by push notificationserver 906. Push filters 914 can include information identifyingapplications that have received authorization to receive pushnotifications on mobile device 100, for example.

In some implementations, push filters 914 can be used by pushnotification server 906 to filter out (e.g., prevent sending) pushnotifications to applications that have not been authorized by a user ofmobile device 100. Each push notification sent by push provider 902 topush notification server 906 can include information (e.g., anidentifier) that identifies the application 908 associated with pushprovider 902 and the mobile device 100 (e.g., device token).

When notification server 906 receives a push notification, notificationserver 906 can use the mobile device identification information (e.g.,device token) to determine which push filters 914 to apply to thereceived push notification. Notification server 906 can compareapplication identification information in the push notification to thepush filters 914 for the identified mobile device to determine if theapplication associated with push provider 902 and identified in the pushnotification is identified in the push filter 914. If the applicationassociated with the push notification is identified in the push filters914, then the notification server 906 can transmit the push notificationreceived from push provider 902 to mobile device 100. If the applicationidentified in the push notification is not identified in the pushfilters 914, then the notification server will not transmit the pushnotification received from push provider 902 to mobile device 100 andcan delete the push notification.

Non-Waking Push Notifications

In some implementations, notification server 906 can be configured toprocess high priority push notifications and low priority pushnotifications. For example, push provider 902 can send a high prioritypush notification 910 and/or a low priority push notification 912 topush notification server 906. Push provider 902 can identify a pushnotification as high or low priority by specifying the priority of thepush notification in data contained within the push notification sent topush notification server 906 and mobile device 100, for example.

In some implementations, push notification server 906 can process lowpriority push notification 912 differently than high priority pushnotification 910. For example, push notification server 906 can beconfigured to compare application identification information containedin high priority push 910 with authorized application identificationinformation in push filters 914 to determine if high priority pushnotification 910 can be transmitted to mobile device 100. If theapplication identification information in high priority pushnotification 910 matches an authorized application identifier in pushfilters 914, then push notification server 906 can transmit the highpriority push notification to mobile device 100. If the applicationidentification information in high priority push notification 910 doesnot match an authorized application identifier in push filters 914, thenpush notification server 906 will not transmit the high priority pushnotification to mobile device 100.

In some implementations, push notification server 906 can be configuredto delay delivery of low priority push notifications. For example, whenmobile device 100 receives a push notification from push notificationserver 906, the receipt of the push notification causes mobile device100 to wake up (e.g., if in a sleep or low power state). When mobiledevice 100 wakes, mobile device 100 will turn on various subsystems andprocessors that can drain the battery, use cellular data, cause themobile device 100 to heat up or otherwise effect the mobile device 100.By preventing or delaying the delivery of low priority pushnotifications to mobile device 100, mobile device 100 can conservenetwork (e.g., cellular data) and system (e.g., battery) resources, forexample.

In some implementations, push notification filters 914 can include awake list 916 and a no wake list 918. The wake list 916 can identifyapplications for which low priority push notifications should bedelivered to mobile device 100. In some implementations, when anapplication is authorized to receive push notifications at mobile device100, the application identification information is added to the wakelist 916 by default. The no wake list 918 can identify authorizedapplications for which low priority push notifications should bedelayed. The specific mechanism for populating no wake list 918 and/ormanipulating wake list 916 and no wake list 918 is described in detailbelow when describing push notification initiated background updates. Insome implementations, high priority push notifications will not bedelayed at the push notification server 906 and will be delivered tomobile device 100 as long as the application identified in the highpriority push notification is identified in push filters 914 (e.g., wakelist 914 and/or no wake list 918).

In some implementations, when push notification server 906 receives alow priority push notification 912, push notification server 906 cancompare the application identifier in low priority push notification 912to wake list 916 and/or no wake list 918. For example, if theapplication identification information in the low priority pushnotification 912 matches an authorized application identifier in thewake list 916, the low priority push notification 912 will be deliveredto the mobile device 100 in a notification message 920.

In some implementations, delivery of low priority push notificationsassociated with applications identified in the no wake list 918 can bedelayed. For example, if an application identified in low priority pushnotification 912 is also identified in no wake list 918, then lowpriority push notification 912 can be stored in push notification datastore 922 and not immediately delivered to mobile device 100. In someimplementations, if the mobile device 100 identified by a pushnotification (high or low priority) is not currently connected to pushnotification server 906, the push notification for the disconnectedmobile device 100 can be stored in push notification data store 922 forlater delivery to mobile device 100.

In some implementations, push notifications stored in push data store922 will remain in push data store 922 until the application identifierassociated with a stored push notification is moved from the no wakelist 918 to wake list 916 or until a network connection is establishedbetween push notification server 906 and mobile device 100. For example,a network connection between push notification server 906 and mobiledevice 100 can be established when another (high or low priority) pushnotification is delivered to mobile device 100 or when mobile device 100sends other transmissions 924 (e.g., status message, heartbeat message,keep alive message, etc.) to push notification server 906. For example,mobile device 100 can send a message 924 to push notification server 905indicating that the mobile device 100 will be active for a period oftime (e.g., 5 minutes) and push notification server 906 can send allreceived push notifications to mobile device 100 during the specifiedactive period of time. In some implementations, when a networkconnection is established between mobile device 100 and pushnotification server 906 all push notifications stored in pushnotification store 922 will be delivered to mobile device 100. Forexample, push notifications stored in push notification data store 922can be transmitted through connections created by other transmissionsbetween mobile device 100 an push notification server 906.

In some implementations, mobile device 100 can establish two differentcommunication channels with push notification server 906. For example,the two communication channels can be established simultaneously or atdifferent times. The mobile device 100 can have a cellular dataconnection and/or a Wi-Fi connection to push notification server 906,for example. In some implementations, mobile device 100 can generate andtransmit to push notification server 906 different push filters 914 foreach communication channel. For example, a cellular data connection canbe associated with first set of push filters 914 for determining when tosend high and low priority push notifications across the cellular dataconnection. A Wi-Fi data connection can be associated with a second setof push filters 914 that are the same or different than the cellulardata push filters for determining when to send high and low prioritypush notifications across the Wi-Fi data connection. When pushnotification server 906 receives a push notification, push notificationserver can compare the application identified in the push notificationto the push notification filters for the communication channel (e.g.,Wi-Fi, cellular) that the push notification server 906 will use totransmit the push notification to the mobile device 100.

Push Initiated Background Updates

In some implementations, receipt of push notifications by mobile device100 can trigger a background update of applications on the mobile device100. For example, when mobile device 100 (e.g., push service daemon 904)receives a push notification message 920 from push notification server906, push service daemon 904 can compare the application identifier inthe push notification message 920 to push filters 928 stored on mobiledevice 100 to determine if the push notification message 920 wasproperly delivered or should have been filtered (e.g., not delivered) bypush notification server 906. For example, push filters 928, wake list930 and no wake list 932 can correspond to push filters 914, wake list916 and no wake list 918, respectively. In some implementations, if pushservice daemon 904 determines that the push notification message 920should not have been delivered to mobile device 100, the pushnotification message 920 will be deleted.

Low Priority Push Notifications

In some implementations, the push notification message 920 received bymobile device 100 can include a low priority push notification. Forexample, the low priority push notification can indicate that contentupdates are available for the application associated with the pushnotification. Thus, when the low priority push notification causes anlaunch of an application 908, the application 908 can download updatedcontent from one or more network resources (e.g., push provider 902).

In some implementations, when push service daemon 904 receives a lowpriority push notification associated with an application (e.g.,application 908) on mobile device 100, push service daemon 904 can asksampling daemon 102 if it is ok to launch the application associatedwith the received low priority push notification. For example, pushservice daemon 904 can invoke the “ok to launch” interface of samplingdaemon 102 by sending sampling daemon 102 an identifier for theapplication associated with the received low priority push notification.Sampling daemon 102 can check data budgets, energy budgets,environmental conditions and rate limits, as described above withreference to FIG. 4, and returns to push service daemon 904 a valueindicating whether it is ok to launch the application identified by thelow priority push notification.

In some implementations, if the value returned from the “ok to launch”request indicates “yes” it is ok to launch the application, push servicedaemon 904 will send the low priority push notification to applicationmanager 106 and application manager 106 can invoke the application(e.g., application 908). Application 908 can then communicate with pushprovider 902 over the network (e.g., the internet) to receive updatedcontent from push provider 902.

In some implementations, if the value returned from the “ok to launch”request indicates “no” it is not ok to launch the application, pushservice daemon 904 will store the low priority push notification in pushnotification data store 934. For example, when storing a low prioritypush notification, push service daemon 904 will only store the last pushnotification received for the application identified in the pushnotification.

In some implementations, when sampling daemon 102 indicates that pushservice daemon 904 should not launch an application right now (e.g., the“ok to launch” reply is “no”), push service daemon 904 can move theapplication identifier for the application from wake list 930 to no wakelist 932. For example, if sampling daemon 102 determines that thebudgets, limits and/or conditions of the mobile device do not allow forlaunching the application, allowing the push notification server 906 towake mobile device 100 for additional low priority push notificationsassociated with the application will just further consume the data andenergy budgets of the mobile device 100 or make environmental conditionsworse (e.g., cause the device to heat up). Thus, by moving theapplication identifier into the no wake list 932 and sending a message926 to push notification server 906 that includes the updated filters928 (e.g., wake list 930 and no wake list 932), notification server 906can update its own push filters 914, wake list 916 and no wake list 918to reflect the changes to push filters 928 and to prevent additional lowpriority push notifications for the application from being delivered tomobile device 100.

In some implementations, if the value returned from the “ok to launch”request indicates that it is “never” ok to launch the application, pushservice daemon 904 will delete the low priority push notification andremove the application identifier associated with the push notificationfrom push filters 928. The updated push filters can be transmitted topush notification server 906 and push filters 914 on push notificationserver 906 can be updated to prevent push notification server 906 fromsending any more push notifications associated with the applicationidentifier.

In some implementations, sampling daemon 102 can transmit a “stop”signal to push service daemon 904 to temporarily prevent future lowpriority push notifications from being sent from push notificationserver 906 to mobile device 100. For example, sampling daemon 102 cansend a stop signal to push service daemon 904 when sampling daemondetermines that the global application launch rate limit has beenexceeded, the push data budget is exhausted for the current hour, thepush energy budget is exhausted for the current hour, the system isexperiencing a thermal event (e.g., mobile device 100 is too hot), themobile device 100 has a poor cellular connection and the mobile device100 is not connected to Wi-Fi and/or that the mobile device 100 isconnected to a voice call and not connected to Wi-Fi. When push servicedaemon 904 receives a stop signal, push service daemon 904 can move theapplication identifiers in wake list 930 to no wake list 932 andtransmit the updated push filters 928 to push notification server 906 toupdate push filters 914. Thus, push notification server 906 willtemporarily prevent future low priority push notifications from wakingmobile device 100 and impacting the budgets, limits and operatingconditions of mobile device 100.

In some implementations, sampling daemon 102 can transmit an “ok toretry” signal to push service daemon 904. For example, sampling daemon102 can monitor the status of the budgets, network connections, limitsand device conditions and will send an “ok to retry” message to pushservice daemon 904 when the push data budget is not exhausted, when theenergy budget is not exhausted, when the mobile device 100 is notexperiencing a thermal event, when the mobile device 100 has a goodquality cellular connection or is connected to Wi-Fi, when mobile device100 is not connected to a voice call and when the launch rate limitshave been reset. Once the push service daemon 904 receives the “ok toretry” signal, push service daemon 904 will send an “ok to launch”request to sampling daemon 102 for each push notification in pushnotification data store 934 to determine if it is ok to launch eachapplication associated with the stored push notifications.

If sampling daemon 102 returns a “yes” from the ok to launch request,push service daemon 904 can send the push notification to applicationmanager 106 and application manager 106 can launch the applicationassociated with the push notification as a background process on mobiledevice 100, as described above. Once the application is launched, theapplication can download content or data updates and update theapplications user interfaces based on the downloaded data. Applicationmanager 106 will not ask sampling daemon 102 if it is ok to launch anapplication associated with a low priority push notification.

High Priority Push Notifications

In some implementations, the push notification message 920 received bymobile device 100 can include a high priority push notification. Forexample, the high priority push notification can indicate that contentupdates are available for the application associated with the pushnotification. Thus, when the high priority push notification causes aninvocation of an application, the application can download updatedcontent from one or more network resources. In some implementations,when a high priority push notification is received by push servicedaemon 904, push service daemon 904 will send the high priority pushnotification to application manager 106 without making an “ok to launch”request to sampling daemon 102.

In some implementations, when application manager 106 receives a pushnotification associated with an application, application manager 106will make an “ok to launch” request to sampling daemon 102. In responseto the “ok to launch” request, sampling daemon 102 can reply with “yes,”“no,” or “never” responses as described above. When application manager106 receives a “yes” reply to the ok to launch request, applicationmanager 106 can launch the application associated with the received highpriority push notification as a background process on mobile device 100.

In some implementations, when application manager 106 receives a “no”reply to an “ok to launch” request, application manager 106 can storethe high priority push notification in high priority push notificationstore 936. When application manager 106 receives a “never” response,application manager 106 can delete the high priority push notificationand delete any push notifications stored in push notification data store936 for the application associated with the push notification.

In some implementations, sampling daemon 102 can send an “ok to retry”signal to application manager 106. For example, when application manager106 receives an “ok to retry” message from sampling daemon 102,application manager 106 can make an “ok to launch” request for theapplications associated with each high priority push notification inhigh priority push notification data store 936 and launch the respectiveapplications as background processes when a “yes” reply is received inresponse to the “ok to launch” request.

Delaying Display of Push Notifications

In some implementations, high priority push notifications can cause agraphical user interface to be displayed on mobile device 100. Forexample, receipt of a high priority push notification can cause abanner, balloon or other graphical object to be displayed on a graphicaluser interface of mobile device 100. The graphical object can includeinformation indicating the subject matter or content of the receivedpush notification, for example.

In some implementations, when application manager 106 receives a highpriority push notification, application manager 106 can cause thenotification to be displayed on a graphical user interface of the mobiledevice 100. However, when the high priority push notification indicatesthat there are data updates to be downloaded to the applicationassociated with the high priority push notification, the application canbe launched in the background of mobile device 100 before the pushnotification is displayed. For example, application manager 106 can beconfigured with an amount of time (e.g., 30 seconds) to delay betweenlaunching an application associated with the high priority pushnotification and displaying the graphical object (e.g., banner) thatannounces the push notification to the user. The delay can allow theapplication enough time to download content updates and update theapplication's user interfaces before being invoked by the user, forexample. Thus, when the user provides input to the graphical object orotherwise invokes the application associated with the high priority pushnotification, the application's user interfaces will be up to date andthe user will not be forced to wait for updates to the application. Insome implementations, if application manager 106 is unable to launch theapplication associated with the high priority push notification, themobile device 100 will display the graphical object (e.g., banner) tonotify the user that the high priority push notification was received.

Example Push Notification Processes

FIG. 10 is a flow diagram of an example process 1000 for performingnon-waking pushes at a push notification server 906. At step 1002, pushnotification server 906 can receive a push notification. For example,push notification server 906 can receive a push notification from a pushnotification provider 902 (e.g., a server operated by an applicationvendor).

At step 1004, push notification server 906 can determine that the pushnotification is a low priority push notification. For example, the pushnotification provider can include data in the push notification thatspecifies the priority of the push notification. Push notificationserver 906 can analyze the contents of the push notification todetermine the priority of the push notification.

At step 1006, push notification server 906 can compare the pushnotification to a push notification filter. For example, the pushnotification can identify an application installed or configured onmobile device 100 to which the low priority push notification isdirected. The push notification can include an application identifier,for example. Push notification server 906 can compare the applicationidentifier in the push notification to application identifiers in thepush notification filter's no wake list 918.

At step 1008, push notification server 906 can determine that the lowpriority push notification should be stored. For example, if theapplication identifier from the low priority push notification is in thepush notification filter's no wake list 918, the push notificationserver 906 can determine that the low priority push should be stored inpush notification data store 922.

At step 1010, based on the determination at step 1008, the low prioritypush notification will be stored in a database or data store 922 of thepush notification server 906 and not immediately sent to the mobiledevice 100.

At step 1012, push notification server 906 can determine that a networkconnection to mobile device 100 has been established. For example, pushnotification server 906 can create a network connection to mobile device100 to deliver another high or low priority push. Mobile device 100 canestablish a network connection to push notification server 906 to sendnotification filter changes, periodic status updates, keep alivemessages or other messages to push notification server 906.

At step 1014, push notification server 906 can send the stored pushnotifications in response to determining that a network connection tomobile device 100 has been established. For example, push notificationserver 906 can send the low priority push notifications stored at thepush notification server 906 to mobile device 100.

FIG. 11 is a flow diagram of an example process 1100 for performingbackground updating of an application in response to a low priority pushnotification. At step 1102, mobile device 100 can receive a low prioritypush notification from push notification server 906.

At step 1104, mobile device 100 can determine if it is ok to launch anapplication associated with the low priority push notification. Forexample, the application can be launched as a background process onmobile device 100. Mobile device 100 can determine whether it is ok tolaunch the application based on data and energy budgets determined forthe mobile device 100. Mobile device 100 can determine whether it is okto launch the application based on conditions of the mobile device,and/or the condition of the mobile device's network connections. Mobiledevice 100 can determine whether it is ok to launch the applicationbased on device-wide (e.g., global) and individual application launchlimits (e.g., how many applications can be launched per hour, how manytimes a single application can be launched per hour). The details fordetermining whether it is ok to launch an application are described ingreater detail with reference to FIG. 4 above.

At step 1106, mobile device 100 can store the low priority pushnotification when device conditions, budgets, limits and other dataindicate that it is not ok to launch the application. For example,mobile device 100 can store the low priority push notifications in adatabase or other data store on mobile device 100.

At step 1108, mobile device 100 can update its push notification filtersin response to determining that it is not ok to launch a backgroundapplication. For example, mobile device 100 can move the applicationassociated with the low priority push notification to the no wake listof the push notification filters on mobile device 100.

At step 1110, mobile device 100 can transmit the updated notificationfilters to push notification server 906. Push notification server 906can update its own push notification filters based on the filtersreceived from mobile device 100 to determine when to transmit and whento not transmit low priority push notifications to mobile device 100.

At step 1112, mobile device 100 can determine that it is ok to retrylaunching applications associated with low priority push notifications.For example, mobile device 100 can determine that the budgets, limitsand device conditions, as described above, allow for launchingadditional background applications on the mobile device 100.

At step 1114, mobile device 100 can determine whether it is ok to launcha particular application associated with a stored low priority pushnotification. For example, mobile device 100 can determine that thebudgets and limits configured on mobile device 100 have been reset orreplenished for the current time and that the environmental conditionsof the mobile device 100 and network connections are good enough tolaunch the particular background application.

At step 1116, mobile device 100 can launch the particular applicationwhen the mobile device 100 determines that it is ok to launch theapplication. For example, the particular application can be launched asa background process to download new content and update the userinterfaces of the application before a user invokes the application.This process will allow a user to invoke an application and not have towait for content updates to be downloaded and for user interfaces of theapplication to be refreshed.

FIG. 12 is a flow diagram of an example process 1200 for performingbackground updating of an application in response to a high prioritypush notification. At step 1202, mobile device 100 can receive a highpriority push notification.

At step 1204, mobile device 100 can determine if it is ok to launch anapplication associated with the high priority push notification. Forexample, mobile device 100 can determine whether it is ok to launch theapplication based on budgets and environmental conditions of the mobiledevice 100 (e.g., device conditions, network conditions, etc.).

At step 1206, mobile device 100 can store the high priority pushnotification when it is not ok to launch the application associated withthe high priority push notification. For example, mobile device 100 canstore the high priority push notification in a database, queue, or otherappropriate data structure.

At step 1208, mobile device 100 can determine that it is ok to retrylaunching applications associated with stored high priority pushnotifications. For example, mobile device 100 can determine that it isok to retry launching applications when the data and energy budgets havebeen replenished, device conditions have improved, network conditionshave improved or other conditions of the mobile device 100 have changed,as discussed above.

At step 1210, mobile device 100 can determine if it is ok to launch anapplication associated with a stored high priority push notification.For example, mobile device 100 can determine if it is ok to launch anapplication based on the criteria discussed above.

At step 1212, mobile device 100 can launch the application in thebackground on the mobile device 100. For example, the application can belaunched as a background process on the mobile device 100 so that theapplication can download updated content from a network resource (e.g.,a content server) on a network (e.g., the internet).

At step 1214, the mobile device 100 can wait a period of time beforepresenting the push notification to the user. For example, the mobiledevice can be configured to allow the application to download contentfor a period of time before notifying the user of the received highpriority push notification.

At step 1216, the mobile device 100 can present the push notification ona user interface of the mobile device 100. For example, the mobiledevice 100 can present a graphical object (e.g., a banner) that includesinformation describing the high priority push notification. The user canselect the graphical object to invoke the application, for example.Since the application had time to download content before the user waspresented with the notification, when the user invokes the applicationthe application will be able to display updated content to the userwithout forcing the user to wait for the updated content to bedownloaded from the network.

Background Uploading/Downloading

FIG. 13 is a block diagram an example system 1300 for performingbackground downloading and/or uploading of data on a mobile device 100.A background download and/or upload can be a network data transfer thatis initiated by an application without explicit input from the user. Forexample, a background download could be performed to retrieve the nextlevel of a video game while the user is playing the video gameapplication. In contrast, a foreground download or upload can be anetwork data transfer performed in response to an explicit indicationfrom the user that the download or upload should occur. For example, aforeground download could be initiated by a user selecting a webpagelink to download a picture, movie or document. Similarly, backgrounduploads can be distinguished from foreground uploads based on whether ornot an explicit user request to upload data to a network resource (e.g.server) was received from the user.

In some implementations, foreground downloads/uploads (e.g.,downloads/uploads explicitly requested by a user) are performedimmediately for the user. For example, the user requesteddownloads/uploads are performed immediately and are not subject tobudgeting constraints or other considerations. Foregrounddownloads/uploads can be performed over a cellular data connection. Incontrast, background downloads and/or uploads can be performedopportunistically and within budgeting constraints and consideringenvironmental conditions, such as the temperature of the mobile device100. In some implementations, background downloads and/or uploads can berestricted to Wi-Fi connections.

In some implementations, system 1300 can include background transferdaemon 1302. In some implementations, background transfer daemon 1302can be configured to perform background downloading and uploading ofdata or content on behalf of applications or processes running on mobiledevice 100. For example background transfer daemon 1302 can performbackground download and/or uploads between application 1304 and server1306 on behalf of application 1304. Thus, the backgrounddownloads/uploads can be performed out of process from application 1304(e.g., not performed in the process requesting the download/upload).

In some implementations, application 1304 can initiate a backgrounddownload/upload by sending a request to background transfer daemon 1302to download or upload data. For example, a request to download data(e.g., content) can identify a network location from where the data canbe downloaded. A request to upload data can identify a network locationto which the data can be uploaded and a location where the data iscurrently stored on the mobile device 100. The request can also identifyapplication 1304. Once the request has been made, application 1304 canbe shut down or suspended so that the application will not continueconsuming computing and/or network resources on mobile device 100 whilethe background download/upload is being performed by background transferdaemon 1302.

In some implementations, upon receiving a request to perform abackground upload or download of data, background transfer daemon 1302can send a request to sampling daemon 102 to determine if it is ok forbackground transfer daemon 1302 to perform a data transfer over thenetwork.

In response to receiving the “ok to transfer” request from backgroundtransfer daemon 1302, sampling daemon 102 can determine if the dataand/or energy budgets for background downloads/uploads have beenexhausted for the current hour. However, if sampling daemon 102determines that the mobile device 100 is connected to an external powersource, sampling daemon 102 will not prevent a backgrounddownload/upload based on the energy budget. Sampling daemon 102 candetermine if mobile device 100 is connected to Wi-Fi. Sampling daemon102 can also determine whether mobile device 100 is in the middle of athermal event (e.g., operating temperature above a predefined thresholdvalue). If sampling daemon 102 determines that the data budget isexhausted and the mobile device 100 is not connected to Wi-Fi, that theenergy budget is exhausted and the mobile device 100 is not connected toan external power source, or that the mobile device 100 is in the middleof a thermal event, then sampling daemon 102 will return a “no” reply tothe “ok to transfer” request by process 1302.

In some implementations, when background transfer daemon 1302 receives a“no” reply to the “ok to transfer” request from sampling daemon 102,process 1302 can store the background download/upload request fromapplication 1304 in request repository 1308.

In some implementations, sampling daemon 102 can send an “ok to retry”signal to background transfer daemon 1302. For example, sampling daemon102 can send the ok to retry signal to background transfer daemon 1302when the data and energy budgets are replenished and when the system isno longer experiencing a thermal event. Sampling daemon 102 can send theok to retry signal to background transfer daemon 1302 when the mobiledevice 100 is connected to Wi-Fi, connected to external power and whenthe system is not experiencing a thermal event.

In some implementations, when the “ok to retry” signal is received bybackground transfer daemon 1302, background transfer daemon 1302 cansend an “ok to transfer” request to sampling daemon 102. If samplingdaemon 102 returns an “ok” reply, background transfer daemon 1302 canperform the background download or upload for application 1304. Once abackground download is completed, background transfer daemon 1302 canwake or invoke application 1304 and provide application 1304 with thedownloaded data.

In some implementations, background transfer daemon 1302 can notifysampling daemon 102 when the background download/upload starts and endsso that sampling daemon 102 can adjust the budgets and maintainstatistics on the background downloads/uploads performed on mobiledevice 100. In some implementations, background transfer daemon 1302 cantransmit the number of bytes transferred over cellular data, over Wi-Fiand/or in total so that sampling daemon 102 can adjust the budgets andmaintain statistics on the background downloads/uploads performed onmobile device 100.

In some implementations, sampling daemon 102 can return a timeout valueto background transfer daemon 1302 in response to an “ok to transfer”request. For example, the timeout value can indicate a period of time(e.g., 5 minutes) that the background transfer daemon has to perform thebackground download or upload. When the timeout period elapses,background transfer daemon 1302 will suspend the background download orupload.

In some implementations, the timeout value can be based on remainingenergy budgets for the current hour. For example, sampling daemon 102can determine how much energy is consumed each second while performing adownload or upload over Wi-Fi based on historical data collected bysampling daemon 102. Sampling daemon 102 can determine the time outperiod by dividing the remaining energy budget by the rate at whichenergy is consumed while performing a background download or upload(e.g., energy budget/energy consumed/time=timeout period).

In some implementations, background downloads and/or uploads areresumable. For example, if mobile device 100 moves out of Wi-Fi range,the background download/upload can be suspended (e.g., paused). Whenmobile device 100 reenters Wi-Fi range, the suspended download/uploadcan be resumed. Similarly, if the background download/upload runs out ofenergy budget (e.g., timeout period elapses), the backgrounddownload/upload can be suspended. When additional budget is allocated(e.g., in the next hour), the suspended download/upload can be resumed.

In some implementations, background downloads/uploads can be suspendedbased on the quality of the network connection. For example, even thoughmobile device 100 can have a good cellular data connection betweenmobile device 100 and the servicing cellular tower and a good dataconnection between the cellular tower and the server that the mobiledevice 100 is transferring data to or from, mobile device 100 may nothave a good connection to the server. For example, the transfer ratebetween the mobile device 100 and the server may be slow or thethroughput of the cellular interface may be low. If the transfer rate ofthe background download/upload falls below a threshold transfer ratevalue and/or the throughput of the background download/upload fallsbelow a threshold throughput value, the background download/upload(e.g., data transfer) can be suspended or paused based on the detectedpoor quality network connection until a better network connection isavailable. For example, if a Wi-Fi connection becomes available thesuspended background download/upload can be resumed over the Wi-Ficonnection.

In some implementations, background transfer daemon 1302 can beconfigured with a limit on the number of background downloads and/oruploads that can be performed at a time. For example, backgroundtransfer daemon 1302 can restrict the number of concurrent backgrounddownloads and/or uploads to three.

Example Background Download/Upload Process

FIG. 14 is flow diagram of an example process 1400 for performingbackground downloads and uploads. For example, background downloadsand/or uploads can be performed on behalf of applications on mobiledevice 100 by background transfer daemon 1302.

At step 1402, a background transfer request can be received. Forexample, background transfer daemon 1302 can receive a backgrounddownload/upload request from an application running on mobile device100. Once the application makes the request, the application can beterminated or suspended, for example. The request can identify theapplication and identify source and/or destination locations for thedata. For example, when downloading data the source location can be anetwork address for a server and the destination location can be adirectory in a file system of the mobile device 100. When uploadingdata, the source location can be a file system location and thedestination can be a network location.

At step 1404, mobile device 100 can determine that budgets and deviceconditions do not allow for the data transfer. For example, backgroundtransfer daemon 1302 can ask sampling daemon 102 if it is ok to performthe requested background transfer. Sampling daemon 102 can determine ifenergy and data budgets for background download/upload are exhausted andif the mobile device 100 is in the middle of a thermal event. If thebackground download/upload budgets are exhausted or if the mobile device100 is in the middle of a thermal event, sampling daemon 102 can send amessage to background transfer daemon 1302 indicating that it is not okto perform the background data transfer.

At step 1406, mobile device 100 can store the background transferrequest. For example, background transfer daemon 1302 can store thetransfer request in a transfer request repository.

At step 1408, mobile device 100 can determine that it is ok to retry thebackground transfer. For example, sampling daemon 102 can determine thatthe data and energy budgets have been replenished and that the mobiledevice 100 is not in the middle of a thermal event Sampling daemon 102can send a retry message to background transfer daemon 1302. Backgroundtransfer daemon 1302 can then attempt to perform the requested transfersstored in the transfer request repository.

At step 1410, mobile device 100 can determine that budgets andconditions of the mobile device 100 allow for background data transfer.For example, background transfer daemon 1302 can ask sampling daemon 102if it is ok to perform the requested background transfer. Samplingdaemon 102 can determine that energy and data budgets for backgrounddownload/upload are replenished and that the mobile device 100 is not inthe middle of a thermal event. If the background download/upload budgetsare not exhausted or if the mobile device 100 is not in the middle of athermal event, sampling daemon 102 can send a message to backgroundtransfer daemon 1302 indicating that it is ok to perform the backgrounddata transfer.

At step 1412, mobile device 100 can perform the background transfer. Forexample, background transfer daemon 1302 can perform the requestedbackground download or background upload for the requesting application.Background transfer daemon 1302 can notify sampling daemon 102 when thebackground transfer begins and ends. Background transfer daemon 1302 cansend a message informing sampling daemon of the number of bytestransferred during the background download or upload. Once thebackground transfer is complete, background transfer daemon 1302 caninvoke (e.g., launch or wake) the application that made the backgroundtransfer request and send completion status information (e.g., success,error, downloaded data, etc.) to the requesting application.

Enabling/Disabling Background Updates

FIG. 15 illustrates an example graphical user interface (GUI) 1500 forenabling and/or disabling background updates for applications on amobile device. For example, GUI 1500 can be an interface presented on adisplay of mobile device 100 for receiving user input to adjustbackground update settings for applications on mobile device 100.

In some implementations, user input to GUI 1500 can enable or disablebackground updates from being performed for applications based on a userinvocation forecast, as described above. For example, sampling process102 and/or application manager 106 can determine whether backgroundupdates are enabled or disabled for an application and prevent theapplication from being launched by application manager 106 or preventthe application from being included in application invocation forecastsgenerated by sampling process 102. For example, if background updatesare disabled for an application, sampling daemon 102 will not includethe application the user invoked application forecast requested by whenapplication manager 106. Thus, application manager 106 will not launchthe application when background updates are disabled. Conversely, ifbackground updates are enabled for the application, the application maybe included in the application invocation forecast generated by samplingdaemon 102 based on user invocation probabilities, as described above.

In some implementations, user input to GUI 1500 can enable or disablebackground updates from being performed for applications when a pushnotification is received, as described above. For example, samplingprocess 102, application manager 106 and/or push service daemon 904 candetermine whether background updates are enabled or disabled for anapplication and prevent the application from being launched byapplication manager 106 in response to receiving a push notification.For example, if background updates are disabled for an application and apush notification is received for the application, application manager106 will not launch the application to download updates in response tothe push notification.

In some implementations, GUI 1500 can display applications 1502-1514that have been configured to perform background updates. For example,the applications 1502-1514 can be configured or programmed to run asbackground processes on mobile device 100 when launched by applicationmanager 106. When run as a background process, the applications1502-1514 can communicate with various network resources to downloadcurrent or updated content. The applications 1502-1514 can then updatetheir respective user interfaces to present updated content when invokedby a user of mobile device 100. In some implementations, applicationsthat are not configured or programmed to perform background updates willnot be displayed on GUI 1500.

In some implementations, a user can provide input to GUI 1500 to enableand/or disable background updates for an application. For example, auser can provide input (e.g., touch input) to mobile device 100 withrespect to toggle 1516 to turn on or off background updates forapplication 1502. A user can provide input (e.g., touch input) to mobiledevice 100 with respect to toggle 1518 to turn on or off backgroundupdates for application 1508.

In some implementations, additional options can be specified for abackground update application through GUI 1500. For example, a user canselect graphical object 1510 associated with application 1514 to invokea graphical user interface (not shown) for specifying additionalbackground update options. The background update options can include,for example, a start time and an end time for turning on and/or offbackground updates for application 1514.

Example System Architecture

FIG. 16 is a block diagram of an example computing device 1600 that canimplement the features and processes of FIGS. 1-15. The computing device1600 can include a memory interface 1602, one or more data processors,image processors and/or central processing units 1604, and a peripheralsinterface 1606. The memory interface 1602, the one or more processors1604 and/or the peripherals interface 1606 can be separate components orcan be integrated in one or more integrated circuits. The variouscomponents in the computing device 1600 can be coupled by one or morecommunication buses or signal lines.

Sensors, devices, and subsystems can be coupled to the peripheralsinterface 1606 to facilitate multiple functionalities. For example, amotion sensor 1610, a light sensor 1612, and a proximity sensor 1614 canbe coupled to the peripherals interface 1606 to facilitate orientation,lighting, and proximity functions. Other sensors 1616 can also beconnected to the peripherals interface 1606, such as a global navigationsatellite system (GNSS) (e.g., GPS receiver), a temperature sensor, abiometric sensor, magnetometer or other sensing device, to facilitaterelated functionalities.

A camera subsystem 1620 and an optical sensor 1622, e.g., a chargedcoupled device (CCD) or a complementary metal-oxide semiconductor (CMOS)optical sensor, can be utilized to facilitate camera functions, such asrecording photographs and video clips. The camera subsystem 1620 and theoptical sensor 1622 can be used to collect images of a user to be usedduring authentication of a user, e.g., by performing facial recognitionanalysis.

Communication functions can be facilitated through one or more wirelesscommunication subsystems 1624, which can include radio frequencyreceivers and transmitters and/or optical (e.g., infrared) receivers andtransmitters. The specific design and implementation of thecommunication subsystem 1624 can depend on the communication network(s)over which the computing device 1600 is intended to operate. Forexample, the computing device 1600 can include communication subsystems1624 designed to operate over a GSM network, a GPRS network, an EDGEnetwork, a Wi-Fi or WiMax network, and a Bluetooth™ network. Inparticular, the wireless communication subsystems 1624 can includehosting protocols such that the device 100 can be configured as a basestation for other wireless devices.

An audio subsystem 1626 can be coupled to a speaker 1628 and amicrophone 1630 to facilitate voice-enabled functions, such as speakerrecognition, voice replication, digital recording, and telephonyfunctions. The audio subsystem 1626 can be configured to facilitateprocessing voice commands, voiceprinting and voice authentication, forexample.

The I/O subsystem 1640 can include a touch-surface controller 1642and/or other input controller(s) 1644. The touch-surface controller 1642can be coupled to a touch surface 1646. The touch surface 1646 andtouch-surface controller 1642 can, for example, detect contact andmovement or break thereof using any of a plurality of touch sensitivitytechnologies, including but not limited to capacitive, resistive,infrared, and surface acoustic wave technologies, as well as otherproximity sensor arrays or other elements for determining one or morepoints of contact with the touch surface 1646.

The other input controller(s) 1644 can be coupled to other input/controldevices 1648, such as one or more buttons, rocker switches, thumb-wheel,infrared port, USB port, and/or a pointer device such as a stylus. Theone or more buttons (not shown) can include an up/down button for volumecontrol of the speaker 1628 and/or the microphone 1630.

In one implementation, a pressing of the button for a first duration candisengage a lock of the touch surface 1646; and a pressing of the buttonfor a second duration that is longer than the first duration can turnpower to the computing device 1600 on or off. Pressing the button for athird duration can activate a voice control, or voice command, modulethat enables the user to speak commands into the microphone 1630 tocause the device to execute the spoken command. The user can customize afunctionality of one or more of the buttons. The touch surface 1646 can,for example, also be used to implement virtual or soft buttons and/or akeyboard.

In some implementations, the computing device 1600 can present recordedaudio and/or video files, such as MP3, AAC, and MPEG files. In someimplementations, the computing device 1600 can include the functionalityof an MP3 player, such as an iPod™.

The memory interface 1602 can be coupled to memory 1650. The memory 1650can include high-speed random access memory and/or non-volatile memory,such as one or more magnetic disk storage devices, one or more opticalstorage devices, and/or flash memory (e.g., NAND, NOR). The memory 1650can store an operating system 1652, such as Darwin. RTXC, LINUX, UNIX,OS X, WINDOWS, or an embedded operating system such as VxWorks.

The operating system 1652 can include instructions for handling basicsystem services and for performing hardware dependent tasks. In someimplementations, the operating system 1652 can be a kernel (e.g., UNIXkernel). In some implementations, the operating system 1652 can includeinstructions for performing dynamic adjustment of the mobile devicebased on user activity. For example, operating system 1652 can implementthe dynamic adjustment features as described with reference to FIGS.1-15.

The memory 1650 can also store communication instructions 1654 tofacilitate communicating with one or more additional devices, one ormore computers and/or one or more servers. The memory 1650 can includegraphical user interface instructions 1656 to facilitate graphic userinterface processing; sensor processing instructions 1658 to facilitatesensor-related processing and functions; phone instructions 1660 tofacilitate phone-related processes and functions; electronic messaginginstructions 1662 to facilitate electronic-messaging related processesand functions; web browsing instructions 1664 to facilitate webbrowsing-related processes and functions; media processing instructions1666 to facilitate media processing-related processes and functions;GNSS/Navigation instructions 1668 to facilitate GNSS andnavigation-related processes and instructions; and/or camerainstructions 1670 to facilitate camera-related processes and functions.

The memory 1650 can store other software instructions 1672 to facilitateother processes and functions, such as the dynamic adjustment processesand functions as described with reference to FIGS. 1-15.

The memory 1650 can also store other software instructions 1674, such asweb video instructions to facilitate web video-related processes andfunctions; and/or web shopping instructions to facilitate webshopping-related processes and functions. In some implementations, themedia processing instructions 1666 are divided into audio processinginstructions and video processing instructions to facilitate audioprocessing-related processes and functions and video processing-relatedprocesses and functions, respectively.

Each of the above identified instructions and applications cancorrespond to a set of instructions for performing one or more functionsdescribed above. These instructions need not be implemented as separatesoftware programs, procedures, or modules. The memory 1650 can includeadditional instructions or fewer instructions. Furthermore, variousfunctions of the computing device 1600 can be implemented in hardwareand/or in software, including in one or more signal processing and/orapplication specific integrated circuits.

What is claimed is:
 1. (canceled)
 2. A method comprising: collecting, bya sampling daemon of a mobile device, historical energy usage statisticsand storing the historical energy usage statistics to a memory of themobile device; determining, by the mobile device, an energy budget forthe mobile device based on the historical energy usage statistics;determining, by the mobile device, a distribution to represent thehistorical energy usage statistics, the distribution having adistribution time period; assigning, by the mobile device, for each timeperiod within the distribution time period, a portion of the energybudget based on energy usage representing a particular time period fromthe historical energy usage statistics; and managing, by the mobiledevice, energy use of the mobile device based on an energy budget of acurrent time period within the distribution.
 3. The method of claim 2,further comprising determining, by the mobile device, whether to launchan application based on the energy budget for the current time period inthe distribution.
 4. The method of claim 2, wherein each time periodequals one hour, and wherein the distribution time period equals 24hours.
 5. The method of claim 2, wherein the energy budget is dividedbetween predictive fetch applications and push applications andbackground download/upload requests.
 6. The method of claim 2, furthercomprising adding, by the mobile device, any unused energy budget fromprevious time periods to the current time period.
 7. The method of claim2, further comprising: receiving, by the sampling daemon, indicationfrom an application manager when an application has been launched andwhen the application has been terminated; determining, by the mobiledevice, an amount of energy that was used by the application based onstart and stop times for the application; and decrementing, by themobile device, the energy budget of the current time period by theamount of energy that was used by the application.
 8. The method ofclaim 2, further comprising: receiving, by the sampling daemon, arequest to launch an application; and denying, by the sampling daemon,the request to launch the application in response to determining thatthe energy budget for the current time period is exhausted.
 9. A systemcomprising: one or more processors; and a computer-readable mediumincluding one or more sequences of instructions which, when executed bythe one or more processors, causes: collecting, by a sampling daemon ofa mobile device, historical energy usage statistics and storing thehistorical energy usage statistics to a memory of the mobile device;determining, by the mobile device, an energy budget for the mobiledevice based on the historical energy usage statistics; determining, bythe mobile device, a distribution to represent the historical energyusage statistics, the distribution having a distribution time period;assigning, by the mobile device, for each time period within thedistribution time period, a portion of the energy budget based on energyusage representing a particular time period from the historical energyusage statistics; and managing, by the mobile device, energy use of themobile device based on an energy budget of a current time period withinthe distribution.
 10. The system of claim 9, wherein the instructionscause determining, by the mobile device, whether to launch anapplication based on the energy budget for the current time period inthe distribution.
 11. The system of claim 9, wherein each time periodequals one hour, and wherein the distribution time period equals 24hours.
 12. The system of claim 9, wherein the energy budget is dividedbetween predictive fetch applications and push applications andbackground download/upload requests.
 13. The system of claim 9, whereinthe instructions cause adding, by the mobile device, any unused energybudget from previous time periods to the current time period.
 14. Thesystem of claim 9, wherein the instructions cause: receiving, by thesampling daemon, indication from an application manager when anapplication has been launched and when the application has beenterminated; determining, by the mobile device, an amount of energy thatwas used by the application based on start and stop times for theapplication; and decrementing, by the mobile device, the energy budgetof the current time period by the amount of energy that was used by theapplication.
 15. The system of claim 9, wherein the instructions cause:receiving, by the sampling daemon, a request to launch an application;and denying, by the sampling daemon, the request to launch theapplication in response to determining that the energy budget for thecurrent time period is exhausted.
 16. A non-transitory computer-readablemedium comprising one or more sequences of instructions which, whenexecuted by one or more processors, causes: collecting, by a samplingdaemon of a mobile device, historical energy usage statistics andstoring the historical energy usage statistics to a memory of the mobiledevice; determining, by the mobile device, an energy budget for themobile device based on the historical energy usage statistics;determining, by the mobile device, a distribution to represent thehistorical energy usage statistics, the distribution having adistribution time period; assigning, by the mobile device, for each timeperiod within the distribution time period, a portion of the energybudget based on energy usage representing a particular time period fromthe historical energy usage statistics; and managing, by the mobiledevice, energy use of the mobile device based on an energy budget of acurrent time period within the distribution.
 17. The non-transitorycomputer-readable medium of claim 16, wherein the instructions causedetermining, by the mobile device, whether to launch an applicationbased on the energy budget for the current time period in thedistribution.
 18. The non-transitory computer-readable medium of claim16, wherein each time period equals one hour, wherein the distributiontime period equals 24 hours, and wherein the energy budget is dividedbetween predictive fetch applications and push applications andbackground download/upload requests.
 19. The non-transitorycomputer-readable medium of claim 16, wherein the instructions causeadding, by the mobile device, any unused energy budget from previoustime periods to the current time period.
 20. The non-transitorycomputer-readable medium of claim 16, wherein the instructions cause:receiving, by the sampling daemon, indication from an applicationmanager when an application has been launched and when the applicationhas been terminated; determining, by the mobile device, an amount ofenergy that was used by the application based on start and stop timesfor the application; and decrementing, by the mobile device, the energybudget of the current time period by the amount of energy that was usedby the application.
 21. The non-transitory computer-readable medium ofclaim 16, wherein the instructions cause: receiving, by the samplingdaemon, a request to launch an application; and denying, by the samplingdaemon, the request to launch the application in response to determiningthat the energy budget for the current time period is exhausted.